lcolladotor@gmail.com -
16 July 2024
+17 July 2024
- Source:vignettes/TenX_data_download.Rmd
+ Source: vignettes/TenX_data_download.Rmd
TenX_data_download.RmdLoad packages## Load packages in the order we'll use them next
library("BiocFileCache")
library("SpatialExperiment")
-#> Warning: package 'S4Vectors' was built under R version 4.4.1
-#> Warning: package 'IRanges' was built under R version 4.4.1
library("rtracklayer")
library("lobstr")
library("spatialLIBD")
@@ -306,12 +304,12 @@ Download spaceranger output files## utils::untar() output status
names(xx) <- basename(names(xx))
xx
-#> V1_Human_Lymph_Node_filtered_feature_bc_matrix.tar.gz.BFC20
-#> 0
-#> V1_Human_Lymph_Node_spatial.tar.gz.BFC21
-#> 0
-#> V1_Human_Lymph_Node_analysis.tar.gz.BFC22
-#> 0
+#> V1_Human_Lymph_Node_filtered_feature_bc_matrix.tar.gz.BFC1
+#> 0
+#> V1_Human_Lymph_Node_spatial.tar.gz.BFC2
+#> 0
+#> V1_Human_Lymph_Node_analysis.tar.gz.BFC3
+#> 0
## List the files we downloaded and extracted
## These files are typically SpaceRanger outputs
@@ -533,8 +531,8 @@ From Gencode## Show the GTF cache location
gtf_cache
-#> BFC23
-#> "/Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/100014a479f08_gencode.v32.annotation.gtf.gz"
+#> BFC4
+#> "/github/home/.cache/R/BiocFileCache/49832febaac_gencode.v32.annotation.gtf.gz"
## Import into R (takes ~1 min)
gtf <- rtracklayer::import(gtf_cache)
@@ -794,7 +792,7 @@ Run the interactive website## Locate our documentation files
docs_path <- system.file("app", "www", package = "spatialLIBD")
docs_path
-#> [1] "/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/spatialLIBD/app/www"
+#> [1] "/__w/_temp/Library/spatialLIBD/app/www"
list.files(docs_path)
#> [1] "documentation_sce_layer.md" "documentation_spe.md"
#> [3] "favicon.ico" "footer.html"
@@ -820,11 +818,11 @@ Wrapper functions= c("lowres", "hires", "detected", "aligned"), load = TRUE,
reference_gtf = gtf_cache
)
-#> 2024-07-16 17:06:02.30044 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
-#> 2024-07-16 17:06:10.20779 read10xVisiumAnalysis: reading analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.42459 add10xVisiumAnalysis: adding analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.61105 rtracklayer::import: reading the reference GTF file
-#> 2024-07-16 17:06:31.708652 adding gene information to the SPE object
+#> 2024-07-17 13:57:08.168846 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
+#> 2024-07-17 13:57:19.596362 read10xVisiumAnalysis: reading analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.702059 add10xVisiumAnalysis: adding analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.945565 rtracklayer::import: reading the reference GTF file
+#> 2024-07-17 13:57:47.519521 adding gene information to the SPE object
#> Warning: Gene IDs did not match. This typically happens when you are not using
#> the same GTF file as the one that was used by SpaceRanger. For example, one
#> file uses GENCODE IDs and the other one ENSEMBL IDs. read10xVisiumWrapper()
@@ -832,7 +830,7 @@ Wrapper functions#> Warning: Dropping 29 out of 36601 genes for which we don't have information on
#> the reference GTF file. This typically happens when you are not using the same
#> GTF file as the one that was used by SpaceRanger.
-#> 2024-07-16 17:06:31.907411 adding information used by spatialLIBD
+#> 2024-07-17 13:57:47.776325 adding information used by spatialLIBD
## Run our shiny app
if (interactive()) {
@@ -1116,200 +1114,202 @@ Reproducibilitylibrary("knitr")
knit("TenX_data_download.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:06:32 EDT"
+#> [1] "2024-07-17 13:57:48 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 1.183 mins
+#> Time difference of 1.705 mins
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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#>
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+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
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@@ -1356,8 +1356,10 @@ Bibliography[5]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[6]
@@ -1385,13 +1387,16 @@ Bibliography[9]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[10]
H. Wickham. lobstr: Visualize R Data Structures with Trees. R
-package version 1.1.2. 2022. URL:
-https://CRAN.R-project.org/package=lobstr.
+package version 1.1.2, https://github.com/r-lib/lobstr. 2022. URL:
+https://lobstr.r-lib.org/.
[11]
@@ -1402,8 +1407,8 @@ Bibliography[12]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[13]
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png
index befc0397..681004b2 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png differ
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png
index 017fcd18..ac8b5fff 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png differ
diff --git a/articles/guide_to_spatial_registration.html b/articles/guide_to_spatial_registration.html
index a056ae9f..cb254465 100644
--- a/articles/guide_to_spatial_registration.html
+++ b/articles/guide_to_spatial_registration.html
@@ -101,9 +101,9 @@ Louise
Development
lahuuki@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/guide_to_spatial_registration.Rmd
+ Source: vignettes/guide_to_spatial_registration.Rmd
guide_to_spatial_registration.Rmd
@@ -268,8 +268,6 @@ Load required packages
library("spatialLIBD")
-#> Warning: package 'S4Vectors' was built under R version 4.4.1
-#> Warning: package 'IRanges' was built under R version 4.4.1
library("SingleCellExperiment")
@@ -290,7 +288,7 @@ Spatial Reference
## get reference layer enrichment statistics
layer_modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:13.829724 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:54:13.294755 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
layer_modeling_results$enrichment[1:5, 1:5]
#> t_stat_WM t_stat_Layer1 t_stat_Layer2 t_stat_Layer3 t_stat_Layer4
@@ -393,18 +391,18 @@ Get Enrichment statistics
gene_ensembl = "gene_id",
gene_name = "gene_name"
)
-#> 2024-07-16 17:04:17.342908 make pseudobulk object
-#> 2024-07-16 17:04:18.696265 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:04:18.724833 drop lowly expressed genes
-#> 2024-07-16 17:04:18.799779 normalize expression
-#> 2024-07-16 17:04:19.584255 create model matrix
-#> 2024-07-16 17:04:19.595618 run duplicateCorrelation()
-#> 2024-07-16 17:04:25.229344 The estimated correlation is: 0.138734774807097
-#> 2024-07-16 17:04:25.231011 computing enrichment statistics
-#> 2024-07-16 17:04:25.960375 extract and reformat enrichment results
-#> 2024-07-16 17:04:26.003855 running the baseline pairwise model
-#> 2024-07-16 17:04:26.12952 computing pairwise statistics
-#> 2024-07-16 17:04:27.403954 computing F-statistics
+#> 2024-07-17 13:54:21.031386 make pseudobulk object
+#> 2024-07-17 13:54:22.727446 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:54:22.789323 drop lowly expressed genes
+#> 2024-07-17 13:54:22.963372 normalize expression
+#> 2024-07-17 13:54:24.427132 create model matrix
+#> 2024-07-17 13:54:24.451001 run duplicateCorrelation()
+#> 2024-07-17 13:54:37.623842 The estimated correlation is: 0.138734774807097
+#> 2024-07-17 13:54:37.626295 computing enrichment statistics
+#> 2024-07-17 13:54:38.79442 extract and reformat enrichment results
+#> 2024-07-17 13:54:38.851417 running the baseline pairwise model
+#> 2024-07-17 13:54:39.041435 computing pairwise statistics
+#> 2024-07-17 13:54:40.421524 computing F-statistics
Extract Enrichment t-statistics
@@ -564,187 +562,189 @@ Reproducibilitylibrary("knitr")
knit("guide_to_spatial_registration.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:28 EDT"
+#> [1] "2024-07-17 13:54:41 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.924 secs
+#> Time difference of 40.965 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
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+#> viridis 0.6.5 2024-01-29 [1] RSPM (R 4.4.0)
+#> viridisLite 0.4.2 2023-05-02 [1] RSPM (R 4.4.0)
+#> withr 3.0.0 2024-01-16 [2] RSPM (R 4.4.0)
+#> xfun 0.45 2024-06-16 [2] RSPM (R 4.4.0)
+#> XML 3.99-0.17 2024-06-25 [1] RSPM (R 4.4.0)
+#> xml2 1.3.6 2023-12-04 [2] RSPM (R 4.4.0)
+#> xtable 1.8-4 2019-04-21 [2] RSPM (R 4.4.0)
+#> XVector 0.44.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
+#> yaml 2.3.9 2024-07-05 [2] RSPM (R 4.4.0)
+#> zlibbioc 1.50.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
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@@ -782,8 +782,10 @@ Bibliography[4]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[5]
@@ -817,8 +819,8 @@ Bibliography[9]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[10]
diff --git a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png
index 37955c4b..d3a2dbfd 100644
Binary files a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png and b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png differ
diff --git a/articles/multi_gene_plots.html b/articles/multi_gene_plots.html
index 684a2bbb..847ca6a7 100644
--- a/articles/multi_gene_plots.html
+++ b/articles/multi_gene_plots.html
@@ -108,9 +108,9 @@ Leonardo
Public Health
lcolladotor@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/multi_gene_plots.Rmd
+ Source: vignettes/multi_gene_plots.Rmd
multi_gene_plots.Rmd
@@ -195,9 +195,9 @@ Plotting One Gene
modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:43.021669 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:06.762958 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
sce_layer <- fetch_data(type = "sce_layer")
-#> 2024-07-16 17:04:43.645201 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:07.675711 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
sig_genes <- sig_genes_extract_all(
n = 400,
modeling_results = modeling_results,
@@ -421,189 +421,191 @@ Reproducibilitylibrary("knitr")
knit("multi_gene_plots.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:53 EDT"
+#> [1] "2024-07-17 13:55:23 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.564 secs
+#> Time difference of 36.887 secs
R session information.
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-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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diff --git a/articles/spatialLIBD.html b/articles/spatialLIBD.html
index 241db4f0..3e707196 100644
--- a/articles/spatialLIBD.html
+++ b/articles/spatialLIBD.html
@@ -114,9 +114,9 @@ Andrew E.
Campus
andrew.jaffe@libd.org
- 16 July 2024
+ 17 July 2024
- Source: vignettes/spatialLIBD.Rmd
+ Source: vignettes/spatialLIBD.Rmd
spatialLIBD.Rmd
@@ -414,7 +414,7 @@ Downloading the data with s
## Download the small example sce data
sce <- fetch_data(type = "sce_example", eh = ehub)
-#> 2024-07-16 17:05:03.908351 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:39.830372 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
## Convert to a SpatialExperiment object
spe <- sce_to_spe(sce)
@@ -426,9 +426,9 @@ Downloading the data with s
## Query ExperimentHub and download the data
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer", eh = ehub)
-#> 2024-07-16 17:05:07.931392 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.107964 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
modeling_results <- fetch_data("modeling_results", eh = ehub)
-#> 2024-07-16 17:05:08.248131 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.559624 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
Once you have downloaded the objects, we can explore them a little
bit
@@ -501,7 +501,7 @@ Downloading the data with s
)
)
#> user system elapsed
-#> 5.090 0.218 5.325
+#> 9.944 0.296 10.247
## Explore the result
class(sig_genes)
@@ -707,7 +707,7 @@ Spot-level genes and continuo
the histology set of purple tones that are noticeable when the
continuous variable is below or equal to the minCount (in
our palettes such points have a 'transparent' color). For
-more details, check the internal code of vis_gene_p().
+more details, check the internal code of vis_gene_p().
Extract significant genes
@@ -1018,7 +1018,7 @@ SpatialExperiment support
As of version 1.3.3, spatialLIBD
supports the SpatialExperiment class from SpatialExperiment.
-The functions vis_gene_p(), vis_gene(),
+The functions vis_gene_p(), vis_gene(),
vis_grid_clus(), vis_grid_gene(),
vis_clus(), vis_clus_p(),
geom_spatial() now work with SpatialExperiment
@@ -1108,7 +1108,7 @@
Generating our data (legacy)vis_clus_p() and
-vis_gene_p(). Having the data from all images in a single
+vis_gene_p(). Having the data from all images in a single
object allows you to use the spot-level data from all images to compute
clusters and do other similar analyses to the ones you would do with
sc/snRNA-seq data. The script creates the
@@ -1377,189 +1377,191 @@ Reproducibilitylibrary("knitr")
knit("spatialLIBD.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:05:18 EDT"
+#> [1] "2024-07-17 13:56:02 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 22.031 secs
+#> Time difference of 34.974 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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+#> zlibbioc 1.50.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -1594,8 +1596,8 @@ Bibliography[4]
W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application
-Framework for R. R package version 1.8.1.1. 2024. URL:
-https://CRAN.R-project.org/package=shiny.
+Framework for R. R package version 1.8.1.1, https://github.com/rstudio/shiny. 2024. URL:
+https://shiny.posit.co/.
[5]
@@ -1616,7 +1618,7 @@ Bibliography[7]
C. Fay, V. Guyader, S. Rochette, et al. golem: A Framework for
Robust Shiny Applications. R package version 0.4.1. 2023. URL:
-https://CRAN.R-project.org/package=golem.
+https://github.com/ThinkR-open/golem.
[8]
@@ -1630,7 +1632,7 @@ Bibliography[9]
C. Gillespie. benchmarkme: Crowd Sourced System Benchmarks. R
package version 1.0.8. 2022. URL:
-https://CRAN.R-project.org/package=benchmarkme.
+https://github.com/csgillespie/benchmarkme.
[10]
@@ -1718,42 +1720,53 @@ Bibliography[20]
M. Morgan, V. Obenchain, J. Hester, et al. SummarizedExperiment:
SummarizedExperiment container. R package version 1.34.0. 2024.
+DOI:
+10.18129/B9.bioc.SummarizedExperiment.
URL:
https://bioconductor.org/packages/SummarizedExperiment.
[21]
M. Morgan and L. Shepherd. AnnotationHub: Client to access
-AnnotationHub resources. R package version 3.12.0. 2024.
+AnnotationHub resources. R package version 3.12.0. 2024. DOI:
+10.18129/B9.bioc.AnnotationHub.
+URL:
+https://bioconductor.org/packages/AnnotationHub.
[22]
M. Morgan and L. Shepherd. ExperimentHub: Client to access
-ExperimentHub resources. R package version 2.12.0. 2024.
+ExperimentHub resources. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.ExperimentHub.
+URL:
+https://bioconductor.org/packages/ExperimentHub.
[23]
E. Neuwirth. RColorBrewer: ColorBrewer Palettes. R package
-version 1.1-3. 2022. URL:
-https://CRAN.R-project.org/package=RColorBrewer.
+version 1.1-3. 2022.
[24]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[25]
J. Ooms. magick: Advanced Graphics and Image-Processing in R. R
-package version 2.8.3. 2024. URL:
-https://CRAN.R-project.org/package=magick.
+package version 2.8.4. 2024. URL:
+https://docs.ropensci.org/magick/https://ropensci.r-universe.dev/magick.
[26]
H. Pagès, M. Lawrence, and P. Aboyoun. S4Vectors: Foundation of
vector-like and list-like containers in Bioconductor. R package
-version 0.42.1. 2024. URL:
+version 0.42.1. 2024. DOI:
+10.18129/B9.bioc.S4Vectors.
+URL:
https://bioconductor.org/packages/S4Vectors.
@@ -1789,7 +1802,10 @@
Bibliography[31]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[32]
@@ -1812,14 +1828,14 @@ Bibliography[35]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[36]
C. Wilke. cowplot: Streamlined Plot Theme and Plot Annotations for
‘ggplot2’. R package version 1.1.3. 2024. URL:
-https://CRAN.R-project.org/package=cowplot.
+https://wilkelab.org/cowplot/.
[37]
@@ -1832,7 +1848,7 @@ Bibliography[38]
Y. Xie, J. Cheng, and X. Tan. DT: A Wrapper of the JavaScript
Library ‘DataTables’. R package version 0.33. 2024. URL:
-https://CRAN.R-project.org/package=DT.
+https://github.com/rstudio/DT.
diff --git a/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png b/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png
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diff --git a/articles/spatialLIBD_files/figure-html/vis_gene-2.png b/articles/spatialLIBD_files/figure-html/vis_gene-2.png
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diff --git a/authors.html b/authors.html
index 3d9fe61e..5953cb2d 100644
--- a/authors.html
+++ b/authors.html
@@ -107,7 +107,7 @@ Authors and Citation
diff --git a/news/index.html b/news/index.html
index 38fa2bfe..93a36916 100644
--- a/news/index.html
+++ b/news/index.html
@@ -63,7 +63,7 @@
@@ -221,7 +221,7 @@ spatialLIBD
-
run_app() now offers the option to chose any of the paletteer::paletteer_d color palettes for discrete variables.
-
-
Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
+Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
-
run_app() now looks for columns that end with ’_colors’ in their name which can be used to pre-specify colors for any companion variables. For example if you have spe$my_groups and spe$my_groups_colors then the second one can specify the colors that will be used for visualizing spe$my_groups. This makes specifying default colors more flexible than before, and the user is still free to change them if necessary.
@@ -265,7 +265,7 @@ spatialLIBD 1
spatialLIBD 1.7.6
NEW FEATURES
-
-
vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
+vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
- The shiny app now has an input controlling the point size. If you increase it to say
5, then if you zoom in the clusters (interactive) panel, you can see larger spots when zooming in.
- These features are related to https://github.com/LieberInstitute/spatialLIBD/issues/28 although the spot diameter is still not the true spot diameter. However, now you have more flexibility for visualizing the spots.
@@ -333,7 +333,7 @@ spatialLIBD
spatialLIBD 1.3.3
NEW FEATURES
-- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
+- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
- Updated citation information to reflect that https://doi.org/10.1038/s41593-020-00787-0 is now public. Also added a link on the README to https://doi.org/10.6084/m9.figshare.13623902.v1 for the manuscript high resolution images.
diff --git a/pkgdown.yml b/pkgdown.yml
index 46fd2df0..f01eec79 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,4 +6,4 @@ articles:
multi_gene_plots: multi_gene_plots.html
spatialLIBD: spatialLIBD.html
TenX_data_download: TenX_data_download.html
-last_built: 2024-07-16T21:00Z
+last_built: 2024-07-17T13:48Z
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diff --git a/reference/Rplot009.png b/reference/Rplot009.png
index 6fde138b..801ff8b6 100644
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diff --git a/reference/Rplot010.png b/reference/Rplot010.png
index 7562a46b..079fa3c9 100644
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diff --git a/reference/add10xVisiumAnalysis.html b/reference/add10xVisiumAnalysis.html
index da55e67a..6dd8b9b8 100644
--- a/reference/add10xVisiumAnalysis.html
+++ b/reference/add10xVisiumAnalysis.html
@@ -65,7 +65,7 @@
Add analysis data from a 10x Genomics Visium experiment to a SPE object
- Source: R/add10xVisiumAnalysis.R
+ Source: R/add10xVisiumAnalysis.R
add10xVisiumAnalysis.Rd
@@ -120,7 +120,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/add_images.html b/reference/add_images.html
index 37749b90..db2faadf 100644
--- a/reference/add_images.html
+++ b/reference/add_images.html
@@ -71,7 +71,7 @@
Add non-standard images with the same dimensions as current ones
- Source: R/add_images.R
+ Source: R/add_images.R
add_images.Rd
@@ -165,30 +165,29 @@ Examples
image_paths = c("151507" = "https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151507_tissue_lowres_image.png")
))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:18.72371 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
-#> 2024-07-16 17:00:29.794628 adding image for sample 151507
-#> 2024-07-16 17:00:30.766353 adding image for sample 151508
+#> 2024-07-17 13:48:26.600477 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:41.90188 adding image for sample 151507
+#> 2024-07-17 13:48:42.538745 adding image for sample 151508
#> Warning: No image was found for sample: 151508
-#> 2024-07-16 17:00:30.766579 adding image for sample 151509
+#> 2024-07-17 13:48:42.539054 adding image for sample 151509
#> Warning: No image was found for sample: 151509
-#> 2024-07-16 17:00:30.766725 adding image for sample 151510
+#> 2024-07-17 13:48:42.539261 adding image for sample 151510
#> Warning: No image was found for sample: 151510
-#> 2024-07-16 17:00:30.766858 adding image for sample 151669
+#> 2024-07-17 13:48:42.539459 adding image for sample 151669
#> Warning: No image was found for sample: 151669
-#> 2024-07-16 17:00:30.76698 adding image for sample 151670
+#> 2024-07-17 13:48:42.539652 adding image for sample 151670
#> Warning: No image was found for sample: 151670
-#> 2024-07-16 17:00:30.767101 adding image for sample 151671
+#> 2024-07-17 13:48:42.539843 adding image for sample 151671
#> Warning: No image was found for sample: 151671
-#> 2024-07-16 17:00:30.767222 adding image for sample 151672
+#> 2024-07-17 13:48:42.540033 adding image for sample 151672
#> Warning: No image was found for sample: 151672
-#> 2024-07-16 17:00:30.76734 adding image for sample 151673
+#> 2024-07-17 13:48:42.540223 adding image for sample 151673
#> Warning: No image was found for sample: 151673
-#> 2024-07-16 17:00:30.767458 adding image for sample 151674
+#> 2024-07-17 13:48:42.540414 adding image for sample 151674
#> Warning: No image was found for sample: 151674
-#> 2024-07-16 17:00:30.767576 adding image for sample 151675
+#> 2024-07-17 13:48:42.540604 adding image for sample 151675
#> Warning: No image was found for sample: 151675
-#> 2024-07-16 17:00:30.767696 adding image for sample 151676
+#> 2024-07-17 13:48:42.540791 adding image for sample 151676
#> Warning: No image was found for sample: 151676
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
diff --git a/reference/add_key.html b/reference/add_key.html
index 7dce6d11..220b5ded 100644
--- a/reference/add_key.html
+++ b/reference/add_key.html
@@ -65,7 +65,7 @@
@@ -124,8 +124,7 @@ Examples
spe$key_original <- NULL
head(spe$key)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:33.017537 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:44.910936 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> [1] "151507_AAACAACGAATAGTTC-1" "151507_AAACAAGTATCTCCCA-1"
#> [3] "151507_AAACAATCTACTAGCA-1" "151507_AAACACCAATAACTGC-1"
#> [5] "151507_AAACAGCTTTCAGAAG-1" "151507_AAACAGGGTCTATATT-1"
diff --git a/reference/add_qc_metrics-1.png b/reference/add_qc_metrics-1.png
index cade42d4..2e65d510 100644
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diff --git a/reference/add_qc_metrics-2.png b/reference/add_qc_metrics-2.png
index 837a248e..d0142804 100644
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diff --git a/reference/add_qc_metrics-3.png b/reference/add_qc_metrics-3.png
index 479ba97d..2b8c7ead 100644
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diff --git a/reference/add_qc_metrics-4.png b/reference/add_qc_metrics-4.png
index cd287d06..39a4439a 100644
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diff --git a/reference/add_qc_metrics-5.png b/reference/add_qc_metrics-5.png
index e6624e22..e1b6345a 100644
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diff --git a/reference/add_qc_metrics-6.png b/reference/add_qc_metrics-6.png
index 95168130..70357959 100644
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diff --git a/reference/add_qc_metrics-7.png b/reference/add_qc_metrics-7.png
index b21b0b71..0a06596e 100644
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diff --git a/reference/add_qc_metrics-8.png b/reference/add_qc_metrics-8.png
index 41ab0f4e..24a2c0e0 100644
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diff --git a/reference/add_qc_metrics.html b/reference/add_qc_metrics.html
index db6a4d92..9c72a786 100644
--- a/reference/add_qc_metrics.html
+++ b/reference/add_qc_metrics.html
@@ -67,7 +67,7 @@
Quality Control for Spatial Data
- Source: R/add_qc_metrics.R
+ Source: R/add_qc_metrics.R
add_qc_metrics.Rd
@@ -144,8 +144,7 @@ Author
Examples
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:43.634355 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f563a40ecf7_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
+#> 2024-07-17 13:49:00.582195 loading file /github/home/.cache/R/BiocFileCache/49872dc0d45_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
diff --git a/reference/annotate_registered_clusters.html b/reference/annotate_registered_clusters.html
index fd6421d6..50b43af5 100644
--- a/reference/annotate_registered_clusters.html
+++ b/reference/annotate_registered_clusters.html
@@ -67,7 +67,7 @@
Annotated spatially-registered clusters
- Source: R/annotate_registered_clusters.R
+ Source: R/annotate_registered_clusters.R
annotate_registered_clusters.Rd
@@ -137,8 +137,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:51.762523 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:13.326528 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/check_modeling_results.html b/reference/check_modeling_results.html
index e56f7419..f95254df 100644
--- a/reference/check_modeling_results.html
+++ b/reference/check_modeling_results.html
@@ -64,7 +64,7 @@
Check input modeling_results
- Source: R/check_modeling_results.R
+ Source: R/check_modeling_results.R
check_modeling_results.Rd
@@ -108,8 +108,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:52.678188 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:14.441658 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Check the object
xx <- check_modeling_results(modeling_results)
diff --git a/reference/check_sce.html b/reference/check_sce.html
index 8a937cdf..fdc02746 100644
--- a/reference/check_sce.html
+++ b/reference/check_sce.html
@@ -66,7 +66,7 @@
@@ -131,8 +131,7 @@ Examples
## Check the object
check_sce(sce_example)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:53.63802 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:15.651297 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
#> class: SingleCellExperiment
#> dim: 33538 47681
#> metadata(1): image
diff --git a/reference/check_sce_layer.html b/reference/check_sce_layer.html
index e6129283..c926c5cf 100644
--- a/reference/check_sce_layer.html
+++ b/reference/check_sce_layer.html
@@ -64,7 +64,7 @@
Check input sce_layer
- Source: R/check_sce_layer.R
+ Source: R/check_sce_layer.R
check_sce_layer.Rd
@@ -112,8 +112,7 @@ Examples
## Obtain example data from the HumanPilot project
## (Maynard, Collado-Torres, et al, 2021)
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:55.536908 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:18.090538 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Check the pseudo-bulked data
check_sce_layer(sce_layer)
diff --git a/reference/check_spe.html b/reference/check_spe.html
index 00f18aab..262e37d5 100644
--- a/reference/check_spe.html
+++ b/reference/check_spe.html
@@ -64,7 +64,7 @@
@@ -123,8 +123,7 @@ Examples
## Check the object
check_spe(spe)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:56.493054 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:19.444343 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> class: SpatialExperiment
#> dim: 33538 47681
#> metadata(0):
diff --git a/reference/cluster_export.html b/reference/cluster_export.html
index 576e5969..41dcf6be 100644
--- a/reference/cluster_export.html
+++ b/reference/cluster_export.html
@@ -67,7 +67,7 @@
Export a column with cluster results
- Source: R/cluster_export.R
+ Source: R/cluster_export.R
cluster_export.Rd
@@ -134,8 +134,7 @@ Examples
cluster_export(spe, "spatialLIBD")
cluster_export(spe, "GraphBased")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:06.836252 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:34.076008 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
diff --git a/reference/cluster_import.html b/reference/cluster_import.html
index feed9a97..585bc91f 100644
--- a/reference/cluster_import.html
+++ b/reference/cluster_import.html
@@ -66,7 +66,7 @@
@@ -137,12 +137,11 @@ Examples
## Re-import them
colData(cluster_import(spe))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:17.501482 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:49.230922 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/spatialLIBD' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/spatialLIBD' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/GraphBased' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/GraphBased' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> DataFrame with 47681 rows and 71 columns
#> key sample_id Cluster sum_umi
diff --git a/reference/enough_ram.html b/reference/enough_ram.html
index 1aefe5c0..17fada89 100644
--- a/reference/enough_ram.html
+++ b/reference/enough_ram.html
@@ -63,7 +63,7 @@
Determine if you have enough RAM memory
- Source: R/enough_ram.R
+ Source: R/enough_ram.R
enough_ram.Rd
diff --git a/reference/fetch_data.html b/reference/fetch_data.html
index 860fcc8a..626b28ea 100644
--- a/reference/fetch_data.html
+++ b/reference/fetch_data.html
@@ -71,7 +71,7 @@
Download the Human DLPFC Visium data from LIBD
- Source: R/fetch_data.R
+ Source: R/fetch_data.R
fetch_data.Rd
@@ -166,8 +166,7 @@ Examples
## Download the SingleCellExperiment object
## at the layer-level
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:28.986594 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:04.599487 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Explore the data
sce_layer
diff --git a/reference/frame_limits.html b/reference/frame_limits.html
index 0a945d2b..ce67964f 100644
--- a/reference/frame_limits.html
+++ b/reference/frame_limits.html
@@ -73,7 +73,7 @@
@@ -154,8 +154,7 @@ Examples
## Obtain the frame limits for one sample
frame_limits(spe, sampleid = "151673")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:30.408348 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:07.106212 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> $y_min
#> [1] 64
#>
diff --git a/reference/gene_set_enrichment.html b/reference/gene_set_enrichment.html
index 58358fa3..69f114cc 100644
--- a/reference/gene_set_enrichment.html
+++ b/reference/gene_set_enrichment.html
@@ -68,7 +68,7 @@
Evaluate the enrichment for a list of gene sets
- Source: R/gene_set_enrichment.R
+ Source: R/gene_set_enrichment.R
gene_set_enrichment.Rd
@@ -176,8 +176,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:40.855511 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:21.075222 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/gene_set_enrichment_plot-1.png b/reference/gene_set_enrichment_plot-1.png
index d68b19ec..d366f433 100644
Binary files a/reference/gene_set_enrichment_plot-1.png and b/reference/gene_set_enrichment_plot-1.png differ
diff --git a/reference/gene_set_enrichment_plot-2.png b/reference/gene_set_enrichment_plot-2.png
index 78df31f0..dbc691ef 100644
Binary files a/reference/gene_set_enrichment_plot-2.png and b/reference/gene_set_enrichment_plot-2.png differ
diff --git a/reference/gene_set_enrichment_plot.html b/reference/gene_set_enrichment_plot.html
index 40392d13..ffdc11f2 100644
--- a/reference/gene_set_enrichment_plot.html
+++ b/reference/gene_set_enrichment_plot.html
@@ -64,7 +64,7 @@
Plot the gene set enrichment results
- Source: R/gene_set_enrichment_plot.R
+ Source: R/gene_set_enrichment_plot.R
gene_set_enrichment_plot.Rd
@@ -178,8 +178,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:41.867526 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:22.531835 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/geom_spatial-1.png b/reference/geom_spatial-1.png
index 64fd3d7a..946c446a 100644
Binary files a/reference/geom_spatial-1.png and b/reference/geom_spatial-1.png differ
diff --git a/reference/geom_spatial.html b/reference/geom_spatial.html
index 5d50b49e..42e5c07c 100644
--- a/reference/geom_spatial.html
+++ b/reference/geom_spatial.html
@@ -66,7 +66,7 @@
A ggplot2 layer for visualizing the Visium histology
- Source: R/geom_spatial.R
+ Source: R/geom_spatial.R
geom_spatial.Rd
@@ -74,7 +74,7 @@ A ggplot2 layer for visualizing the Visium histology
This function defines a ggplot2::layer() for visualizing the histology
image from Visium. It can be combined with other ggplot2 functions for
visualizing the clusters as in vis_clus_p() or gene-level information
-as in vis_gene_p().
+as in vis_gene_p().
@@ -175,8 +175,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:43.207432 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:24.396394 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/get_colors.html b/reference/get_colors.html
index e49a44bf..dfbeb5c2 100644
--- a/reference/get_colors.html
+++ b/reference/get_colors.html
@@ -64,7 +64,7 @@
Obtain the colors for a set of cluster names
- Source: R/get_colors.R
+ Source: R/get_colors.R
get_colors.Rd
@@ -84,7 +84,7 @@ Arguments
- colors
A vector of colors. If NULL then a set of default colors will
be used when clusters has less than 12 unique values, otherwise
-Polychrome::palette36 will be used which can
+Polychrome::palette36 will be used which can
generate up to 36 unique colors. If the number of unique clusters is beyond
36 then this function will fail.
Examples
## Obtain the necessary data
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:54.433623 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:39.853193 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Example layer colors with the corresponding names
get_colors(libd_layer_colors, sce_layer$layer_guess)
diff --git a/reference/img_edit-1.png b/reference/img_edit-1.png
index 94154fc3..9af3f312 100644
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diff --git a/reference/img_edit.html b/reference/img_edit.html
index 9df344ec..004b6d82 100644
--- a/reference/img_edit.html
+++ b/reference/img_edit.html
@@ -65,7 +65,7 @@
@@ -222,8 +222,7 @@ Examples
x <- img_edit(spe, sampleid = "151507", brightness = 25)
plot(x)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:56.683064 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:41.084926 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/img_update.html b/reference/img_update.html
index 5b6a0f39..5d92fe1f 100644
--- a/reference/img_update.html
+++ b/reference/img_update.html
@@ -63,7 +63,7 @@
@@ -139,8 +139,7 @@ Examples
## Reduce brightness to 25% and update the imgData()
imgData(img_update(spe, sampleid = "151507", brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:07.614049 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:56.77859 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/img_update_all.html b/reference/img_update_all.html
index e322e40f..8a0c7996 100644
--- a/reference/img_update_all.html
+++ b/reference/img_update_all.html
@@ -65,7 +65,7 @@
Update the images for all samples
- Source: R/img_update_all.R
+ Source: R/img_update_all.R
img_update_all.Rd
@@ -138,8 +138,7 @@ Examples
## update the imgData()
imgData(img_update_all(spe, brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:17.633699 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:11.011904 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 24 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/index.html b/reference/index.html
index 3d629a4c..fdcce2ae 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -249,6 +249,10 @@ All functions vis_gene()
Sample spatial gene visualization
+
+
+ Sample spatial gene visualization workhorse function
diff --git a/reference/layer_boxplot-1.png b/reference/layer_boxplot-1.png
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index a10d0a22..96e6f0bb 100644
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diff --git a/reference/layer_boxplot-5.png b/reference/layer_boxplot-5.png
index 14ac9b54..c8eb3bae 100644
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diff --git a/reference/layer_boxplot-6.png b/reference/layer_boxplot-6.png
index f44309f3..5dea49a5 100644
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diff --git a/reference/layer_boxplot-7.png b/reference/layer_boxplot-7.png
index f6564386..a247b555 100644
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diff --git a/reference/layer_boxplot.html b/reference/layer_boxplot.html
index 90de61cd..302acf11 100644
--- a/reference/layer_boxplot.html
+++ b/reference/layer_boxplot.html
@@ -65,7 +65,7 @@
Layer-level (group-level) boxplots
- Source: R/layer_boxplot.R
+ Source: R/layer_boxplot.R
layer_boxplot.Rd
@@ -185,11 +185,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:28.442408 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:28.503014 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:29.096088 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:29.384093 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Top 2 genes from the enrichment model
sig_genes <- sig_genes_extract_all(
diff --git a/reference/layer_matrix_plot-1.png b/reference/layer_matrix_plot-1.png
index d9460395..4f269d7a 100644
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diff --git a/reference/layer_matrix_plot-2.png b/reference/layer_matrix_plot-2.png
index 8e3e7d6d..2f29029a 100644
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diff --git a/reference/layer_matrix_plot.html b/reference/layer_matrix_plot.html
index d2728bb4..d5cd6750 100644
--- a/reference/layer_matrix_plot.html
+++ b/reference/layer_matrix_plot.html
@@ -66,7 +66,7 @@
Visualize a matrix of values across human brain layers
- Source: R/layer_matrix_plot.R
+ Source: R/layer_matrix_plot.R
layer_matrix_plot.Rd
diff --git a/reference/layer_stat_cor.html b/reference/layer_stat_cor.html
index be43eee0..208b193a 100644
--- a/reference/layer_stat_cor.html
+++ b/reference/layer_stat_cor.html
@@ -63,7 +63,7 @@
Layer modeling correlation of statistics
- Source: R/layer_stat_cor.R
+ Source: R/layer_stat_cor.R
layer_stat_cor.Rd
@@ -156,8 +156,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:31.53213 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:32.756558 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/layer_stat_cor_plot-1.png b/reference/layer_stat_cor_plot-1.png
index 5019ec42..72baf49d 100644
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diff --git a/reference/layer_stat_cor_plot-3.png b/reference/layer_stat_cor_plot-3.png
index c9a9bcf0..4b97784a 100644
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diff --git a/reference/layer_stat_cor_plot-4.png b/reference/layer_stat_cor_plot-4.png
index ee32ca9a..d74ca04c 100644
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diff --git a/reference/layer_stat_cor_plot-5.png b/reference/layer_stat_cor_plot-5.png
index 2e2b880f..a6ca399d 100644
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diff --git a/reference/layer_stat_cor_plot.html b/reference/layer_stat_cor_plot.html
index d08a54a2..7670f03a 100644
--- a/reference/layer_stat_cor_plot.html
+++ b/reference/layer_stat_cor_plot.html
@@ -66,7 +66,7 @@
Visualize the layer modeling correlation of statistics
- Source: R/layer_stat_cor_plot.R
+ Source: R/layer_stat_cor_plot.R
layer_stat_cor_plot.Rd
@@ -145,8 +145,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:32.436771 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:33.883339 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/libd_layer_colors.html b/reference/libd_layer_colors.html
index d2df282e..6a843fec 100644
--- a/reference/libd_layer_colors.html
+++ b/reference/libd_layer_colors.html
@@ -64,7 +64,7 @@
diff --git a/reference/locate_images.html b/reference/locate_images.html
index 62727198..8cbe293c 100644
--- a/reference/locate_images.html
+++ b/reference/locate_images.html
@@ -65,7 +65,7 @@
diff --git a/reference/multi_gene_pca.html b/reference/multi_gene_pca.html
index 58575a98..334fbe7d 100644
--- a/reference/multi_gene_pca.html
+++ b/reference/multi_gene_pca.html
@@ -68,7 +68,7 @@
Combine multiple continuous variables through PCA
- Source: R/multi_gene_pca.R
+ Source: R/multi_gene_pca.R
multi_gene_pca.Rd
diff --git a/reference/multi_gene_sparsity.html b/reference/multi_gene_sparsity.html
index 042ec2af..2ababa43 100644
--- a/reference/multi_gene_sparsity.html
+++ b/reference/multi_gene_sparsity.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by proportion of positive values
- Source: R/multi_gene_sparsity.R
+ Source: R/multi_gene_sparsity.R
multi_gene_sparsity.Rd
diff --git a/reference/multi_gene_z_score.html b/reference/multi_gene_z_score.html
index 612273f5..ce8a878a 100644
--- a/reference/multi_gene_z_score.html
+++ b/reference/multi_gene_z_score.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by averaging Z scores
- Source: R/multi_gene_z_score.R
+ Source: R/multi_gene_z_score.R
multi_gene_z_score.Rd
diff --git a/reference/prep_stitched_data.html b/reference/prep_stitched_data.html
index 0c4a592e..36678e3a 100644
--- a/reference/prep_stitched_data.html
+++ b/reference/prep_stitched_data.html
@@ -68,7 +68,7 @@
Prepare stitched data for plotting
- Source: R/prep_stitched_data.R
+ Source: R/prep_stitched_data.R
prep_stitched_data.Rd
diff --git a/reference/read10xVisiumAnalysis.html b/reference/read10xVisiumAnalysis.html
index b36ef451..7e04bd5b 100644
--- a/reference/read10xVisiumAnalysis.html
+++ b/reference/read10xVisiumAnalysis.html
@@ -64,7 +64,7 @@
Load analysis data from a 10x Genomics Visium experiment
- Source: R/read10xVisiumAnalysis.R
+ Source: R/read10xVisiumAnalysis.R
read10xVisiumAnalysis.Rd
@@ -118,7 +118,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/read10xVisiumWrapper.html b/reference/read10xVisiumWrapper.html
index 56b267a0..c8d01991 100644
--- a/reference/read10xVisiumWrapper.html
+++ b/reference/read10xVisiumWrapper.html
@@ -66,7 +66,7 @@
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
- Source: R/read10xVisiumWrapper.R
+ Source: R/read10xVisiumWrapper.R
read10xVisiumWrapper.Rd
@@ -162,7 +162,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/registration_block_cor.html b/reference/registration_block_cor.html
index 33000024..126fabd2 100644
--- a/reference/registration_block_cor.html
+++ b/reference/registration_block_cor.html
@@ -66,7 +66,7 @@
Spatial registration: block correlation
- Source: R/registration_block_cor.R
+ Source: R/registration_block_cor.R
registration_block_cor.Rd
@@ -121,36 +121,36 @@ See also
Examples
example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:34.847415 make pseudobulk object
-#> 2024-07-16 17:02:34.953364 drop lowly expressed genes
-#> 2024-07-16 17:02:34.99097 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:37.088175 make pseudobulk object
+#> 2024-07-17 13:51:37.267087 drop lowly expressed genes
+#> 2024-07-17 13:51:37.336566 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -179,10 +179,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:35.032307 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:37.415555 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -198,8 +198,8 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:35.038484 run duplicateCorrelation()
-#> 2024-07-16 17:02:35.564971 The estimated correlation is: -0.0187869166526901
+#> 2024-07-17 13:51:37.428263 run duplicateCorrelation()
+#> 2024-07-17 13:51:38.691552 The estimated correlation is: -0.0187869166526901
diff --git a/reference/registration_model.html b/reference/registration_model.html
index 7a26252f..c96dc0da 100644
--- a/reference/registration_model.html
+++ b/reference/registration_model.html
@@ -67,7 +67,7 @@
Spatial registration: model
- Source: R/registration_model.R
+ Source: R/registration_model.R
registration_model.Rd
@@ -125,34 +125,34 @@ See also
Examples
example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:35.873124 make pseudobulk object
-#> 2024-07-16 17:02:35.960837 drop lowly expressed genes
-#> 2024-07-16 17:02:35.986325 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:39.129951 make pseudobulk object
+#> 2024-07-17 13:51:39.31554 drop lowly expressed genes
+#> 2024-07-17 13:51:39.370617 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -181,7 +181,7 @@ Examples
#> D_S S D 14
#> E_S S E 11
registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:36.024617 create model matrix
+#> 2024-07-17 13:51:39.447064 create model matrix
head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
diff --git a/reference/registration_pseudobulk.html b/reference/registration_pseudobulk.html
index 653d03b2..8722ef39 100644
--- a/reference/registration_pseudobulk.html
+++ b/reference/registration_pseudobulk.html
@@ -64,7 +64,7 @@
Spatial registration: pseudobulk
- Source: R/registration_pseudobulk.R
+ Source: R/registration_pseudobulk.R
registration_pseudobulk.Rd
@@ -159,9 +159,9 @@ Examples
## Pseudo-bulk
sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.341187 make pseudobulk object
-#> 2024-07-16 17:02:36.4321 drop lowly expressed genes
-#> 2024-07-16 17:02:36.458483 normalize expression
+#> 2024-07-17 13:51:39.903902 make pseudobulk object
+#> 2024-07-17 13:51:40.056716 drop lowly expressed genes
+#> 2024-07-17 13:51:40.111023 normalize expression
colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
diff --git a/reference/registration_stats_anova.html b/reference/registration_stats_anova.html
index 1cf15645..cdc9d765 100644
--- a/reference/registration_stats_anova.html
+++ b/reference/registration_stats_anova.html
@@ -66,7 +66,7 @@
Spatial registration: compute ANOVA statistics
- Source: R/registration_stats_anova.R
+ Source: R/registration_stats_anova.R
registration_stats_anova.Rd
@@ -153,38 +153,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.908 make pseudobulk object
-#> 2024-07-16 17:02:36.981269 drop lowly expressed genes
-#> 2024-07-16 17:02:37.007143 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:40.701746 make pseudobulk object
+#> 2024-07-17 13:51:40.884268 drop lowly expressed genes
+#> 2024-07-17 13:51:40.939518 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -213,10 +213,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:37.061168 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:41.012467 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -232,14 +232,14 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:37.066375 run duplicateCorrelation()
-#> 2024-07-16 17:02:37.583667 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:41.024125 run duplicateCorrelation()
+#> 2024-07-17 13:51:42.289985 The estimated correlation is: -0.0187869166526901
results_anova <- registration_stats_anova(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.589856 computing F-statistics
+#> 2024-07-17 13:51:42.302664 computing F-statistics
head(results_anova)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1328075 0.93918553 0.9951876 5.499488 ENSG1 gene1
@@ -254,7 +254,7 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.615244 computing F-statistics
+#> 2024-07-17 13:51:42.365534 computing F-statistics
head(results_anova_nan)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1357180 0.93736053 0.9943765 5.499488 ENSG1 gene1
@@ -276,7 +276,7 @@ Examples
covars = NULL,
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "nocovar"
)
-#> 2024-07-16 17:02:37.632809 computing F-statistics
+#> 2024-07-17 13:51:42.415614 computing F-statistics
head(results_anova_nocovar)
#> f_stat_nocovar p_value_nocovar fdr_nocovar AveExpr_nocovar ensembl gene
#> 1 0.1393641 0.9351345 0.9962097 5.499488 ENSG1 gene1
diff --git a/reference/registration_stats_enrichment.html b/reference/registration_stats_enrichment.html
index c2fc717e..b97c7f9c 100644
--- a/reference/registration_stats_enrichment.html
+++ b/reference/registration_stats_enrichment.html
@@ -65,7 +65,7 @@
Spatial registration: compute enrichment statistics
- Source: R/registration_stats_enrichment.R
+ Source: R/registration_stats_enrichment.R
registration_stats_enrichment.Rd
@@ -144,38 +144,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:37.992936 make pseudobulk object
-#> 2024-07-16 17:02:38.06571 drop lowly expressed genes
-#> 2024-07-16 17:02:38.091375 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:42.992514 make pseudobulk object
+#> 2024-07-17 13:51:43.146693 drop lowly expressed genes
+#> 2024-07-17 13:51:43.201202 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -204,10 +204,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:38.129501 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:43.274381 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -223,15 +223,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:38.134799 run duplicateCorrelation()
-#> 2024-07-16 17:02:38.654908 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:43.285637 run duplicateCorrelation()
+#> 2024-07-17 13:51:44.583617 The estimated correlation is: -0.0187869166526901
results_enrichment <- registration_stats_enrichment(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.657236 computing enrichment statistics
-#> 2024-07-16 17:02:38.701689 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.587859 computing enrichment statistics
+#> 2024-07-17 13:51:44.705956 extract and reformat enrichment results
head(results_enrichment)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1482017 0.5610669 -0.3612235 -0.3458508 0.88374480 0.58130631
@@ -260,8 +260,8 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.712787 computing enrichment statistics
-#> 2024-07-16 17:02:38.771541 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.739083 computing enrichment statistics
+#> 2024-07-17 13:51:44.842281 extract and reformat enrichment results
head(results_enrichment_nan)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1497747 0.56711100 -0.3650801 -0.3495404 0.88252049 0.57727506
diff --git a/reference/registration_stats_pairwise.html b/reference/registration_stats_pairwise.html
index c11a5e44..03bff131 100644
--- a/reference/registration_stats_pairwise.html
+++ b/reference/registration_stats_pairwise.html
@@ -66,7 +66,7 @@
Spatial registration: compute pairwise statistics
- Source: R/registration_stats_pairwise.R
+ Source: R/registration_stats_pairwise.R
registration_stats_pairwise.Rd
@@ -146,38 +146,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:39.085978 make pseudobulk object
-#> 2024-07-16 17:02:39.159736 drop lowly expressed genes
-#> 2024-07-16 17:02:39.185678 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:45.303165 make pseudobulk object
+#> 2024-07-17 13:51:45.456984 drop lowly expressed genes
+#> 2024-07-17 13:51:45.511196 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -206,10 +206,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:39.224065 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:45.621594 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -225,15 +225,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:39.22931 run duplicateCorrelation()
-#> 2024-07-16 17:02:39.781072 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:45.632849 run duplicateCorrelation()
+#> 2024-07-17 13:51:46.88774 The estimated correlation is: -0.0187869166526901
results_pairwise <- registration_stats_pairwise(sce_pseudo,
registration_mod, block_cor,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.782515 running the baseline pairwise model
-#> 2024-07-16 17:02:39.790292 computing pairwise statistics
+#> 2024-07-17 13:51:46.889688 running the baseline pairwise model
+#> 2024-07-17 13:51:46.906431 computing pairwise statistics
head(results_pairwise)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2393683 0.29771391 0.28880637 0.5370822 0.5281747
@@ -277,8 +277,8 @@ Examples
block_cor = NaN,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.811874 running the baseline pairwise model
-#> 2024-07-16 17:02:39.818697 computing pairwise statistics
+#> 2024-07-17 13:51:46.971696 running the baseline pairwise model
+#> 2024-07-17 13:51:46.989106 computing pairwise statistics
head(results_pairwise_nan)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2419770 0.30095840 0.29195379 0.5429354 0.5339308
diff --git a/reference/registration_wrapper.html b/reference/registration_wrapper.html
index 546b32eb..a04252d2 100644
--- a/reference/registration_wrapper.html
+++ b/reference/registration_wrapper.html
@@ -68,7 +68,7 @@
Spatial registration: wrapper function
- Source: R/registration_wrapper.R
+ Source: R/registration_wrapper.R
registration_wrapper.Rd
@@ -200,18 +200,18 @@ Examples
sce,
"Cell_Cycle", "sample_id", c("age"), "ensembl", "gene_name", "wrapper"
)
-#> 2024-07-16 17:02:40.149028 make pseudobulk object
-#> 2024-07-16 17:02:40.221379 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:02:40.231996 drop lowly expressed genes
-#> 2024-07-16 17:02:40.27465 normalize expression
-#> 2024-07-16 17:02:40.303232 create model matrix
-#> 2024-07-16 17:02:40.308019 run duplicateCorrelation()
-#> 2024-07-16 17:02:41.300298 The estimated correlation is: -0.0783081238514527
-#> 2024-07-16 17:02:41.301437 computing enrichment statistics
-#> 2024-07-16 17:02:41.342436 extract and reformat enrichment results
-#> 2024-07-16 17:02:41.35071 running the baseline pairwise model
-#> 2024-07-16 17:02:41.357315 computing pairwise statistics
-#> 2024-07-16 17:02:41.380689 computing F-statistics
+#> 2024-07-17 13:51:47.541862 make pseudobulk object
+#> 2024-07-17 13:51:47.707925 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:51:47.729853 drop lowly expressed genes
+#> 2024-07-17 13:51:47.785167 normalize expression
+#> 2024-07-17 13:51:47.8429 create model matrix
+#> 2024-07-17 13:51:47.853499 run duplicateCorrelation()
+#> 2024-07-17 13:51:50.267571 The estimated correlation is: -0.0783081238514532
+#> 2024-07-17 13:51:50.269845 computing enrichment statistics
+#> 2024-07-17 13:51:50.386595 extract and reformat enrichment results
+#> 2024-07-17 13:51:50.412505 running the baseline pairwise model
+#> 2024-07-17 13:51:50.430847 computing pairwise statistics
+#> 2024-07-17 13:51:50.505218 computing F-statistics
diff --git a/reference/run_app.html b/reference/run_app.html
index d23cb924..2cca4ddc 100644
--- a/reference/run_app.html
+++ b/reference/run_app.html
@@ -65,7 +65,7 @@
@@ -270,7 +270,7 @@ Examples
vars <- colnames(colData(spe))
## Set default cluster colors
- colors_BayesSpace <- Polychrome::palette36.colors(28)
+ colors_BayesSpace <- Polychrome::palette36.colors(28)
names(colors_BayesSpace) <- c(1:28)
m <- match(as.character(spe$BayesSpace_harmony_09), names(colors_BayesSpace))
stopifnot(all(!is.na(m)))
diff --git a/reference/sce_to_spe.html b/reference/sce_to_spe.html
index 84fd3093..e0797fb6 100644
--- a/reference/sce_to_spe.html
+++ b/reference/sce_to_spe.html
@@ -67,7 +67,7 @@
@@ -127,8 +127,7 @@ Examples
## Transform it to a SpatialExperiment object
spe <- sce_to_spe(sce)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:43.103369 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:52.727073 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/sig_genes_extract.html b/reference/sig_genes_extract.html
index 0ecdbcc3..4c448c85 100644
--- a/reference/sig_genes_extract.html
+++ b/reference/sig_genes_extract.html
@@ -67,7 +67,7 @@
Extract significant genes
- Source: R/sig_genes_extract.R
+ Source: R/sig_genes_extract.R
sig_genes_extract.Rd
@@ -156,11 +156,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:52.484674 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:05.714888 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:53.182388 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:06.659035 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## anova top 10 genes
sig_genes_extract(
diff --git a/reference/sig_genes_extract_all.html b/reference/sig_genes_extract_all.html
index 17516a57..4a42f61e 100644
--- a/reference/sig_genes_extract_all.html
+++ b/reference/sig_genes_extract_all.html
@@ -65,7 +65,7 @@
Extract significant genes for all modeling results
- Source: R/sig_genes_extract_all.R
+ Source: R/sig_genes_extract_all.R
sig_genes_extract_all.Rd
@@ -128,11 +128,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.422915 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:10.311903 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.970561 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:11.371345 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## top 10 genes for all models
sig_genes_extract_all(
diff --git a/reference/sort_clusters.html b/reference/sort_clusters.html
index 8dccd3d7..675c4397 100644
--- a/reference/sort_clusters.html
+++ b/reference/sort_clusters.html
@@ -65,7 +65,7 @@
diff --git a/reference/spatialLIBD-package.html b/reference/spatialLIBD-package.html
index 148e52f3..c22a18c2 100644
--- a/reference/spatialLIBD-package.html
+++ b/reference/spatialLIBD-package.html
@@ -64,7 +64,7 @@
spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
- Source: R/spatialLIBD-package.R
+ Source: R/spatialLIBD-package.R
spatialLIBD-package.Rd
diff --git a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
index e6a4ba86..4dbbeb2a 100644
--- a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
+++ b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
@@ -69,7 +69,7 @@
Cell cluster t-statistics from Tran et al
- Source: R/data.R
+ Source: R/data.R
tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.Rd
diff --git a/reference/vis_clus-1.png b/reference/vis_clus-1.png
index b62ae3bc..fff9298e 100644
Binary files a/reference/vis_clus-1.png and b/reference/vis_clus-1.png differ
diff --git a/reference/vis_clus-2.png b/reference/vis_clus-2.png
index 59f18aa4..4962aaef 100644
Binary files a/reference/vis_clus-2.png and b/reference/vis_clus-2.png differ
diff --git a/reference/vis_clus-3.png b/reference/vis_clus-3.png
index ac93117a..3a3d3926 100644
Binary files a/reference/vis_clus-3.png and b/reference/vis_clus-3.png differ
diff --git a/reference/vis_clus-4.png b/reference/vis_clus-4.png
index 7a08ba8a..fd74eca4 100644
Binary files a/reference/vis_clus-4.png and b/reference/vis_clus-4.png differ
diff --git a/reference/vis_clus.html b/reference/vis_clus.html
index 4c441931..29b47fed 100644
--- a/reference/vis_clus.html
+++ b/reference/vis_clus.html
@@ -65,7 +65,7 @@
@@ -242,8 +242,7 @@ Examples
)
print(p4)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:57.892758 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:14.053539 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_clus_p-1.png b/reference/vis_clus_p-1.png
index ac93117a..3a3d3926 100644
Binary files a/reference/vis_clus_p-1.png and b/reference/vis_clus_p-1.png differ
diff --git a/reference/vis_clus_p.html b/reference/vis_clus_p.html
index 0106b4be..1e416396 100644
--- a/reference/vis_clus_p.html
+++ b/reference/vis_clus_p.html
@@ -66,7 +66,7 @@
Sample spatial cluster visualization workhorse function
- Source: R/vis_clus_p.R
+ Source: R/vis_clus_p.R
vis_clus_p.Rd
@@ -74,7 +74,7 @@ Sample spatial cluster visualization workhorse function
This function visualizes the clusters for one given sample at the spot-level
using (by default) the histology information on the background. This is the
function that does all the plotting behind vis_clus(). To visualize
-gene-level (or any continuous variable) use vis_gene_p().
+gene-level (or any continuous variable) use vis_gene_p().
@@ -202,8 +202,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:52:33.265544 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene-1.png b/reference/vis_gene-1.png
index dd3f3f08..3585ea9b 100644
Binary files a/reference/vis_gene-1.png and b/reference/vis_gene-1.png differ
diff --git a/reference/vis_gene-10.png b/reference/vis_gene-10.png
index fe1916ef..a44ac448 100644
Binary files a/reference/vis_gene-10.png and b/reference/vis_gene-10.png differ
diff --git a/reference/vis_gene-2.png b/reference/vis_gene-2.png
index e31f94d3..7da9ccfd 100644
Binary files a/reference/vis_gene-2.png and b/reference/vis_gene-2.png differ
diff --git a/reference/vis_gene-3.png b/reference/vis_gene-3.png
index ad0dd5f5..e4286c69 100644
Binary files a/reference/vis_gene-3.png and b/reference/vis_gene-3.png differ
diff --git a/reference/vis_gene-4.png b/reference/vis_gene-4.png
index 55d24ff4..1ff3e170 100644
Binary files a/reference/vis_gene-4.png and b/reference/vis_gene-4.png differ
diff --git a/reference/vis_gene-5.png b/reference/vis_gene-5.png
index c1e58e44..6cbbe839 100644
Binary files a/reference/vis_gene-5.png and b/reference/vis_gene-5.png differ
diff --git a/reference/vis_gene-6.png b/reference/vis_gene-6.png
index 528c1c2a..9eccafab 100644
Binary files a/reference/vis_gene-6.png and b/reference/vis_gene-6.png differ
diff --git a/reference/vis_gene-7.png b/reference/vis_gene-7.png
index da60a0bf..c26013a0 100644
Binary files a/reference/vis_gene-7.png and b/reference/vis_gene-7.png differ
diff --git a/reference/vis_gene-8.png b/reference/vis_gene-8.png
index 2e73ba4d..a91893cf 100644
Binary files a/reference/vis_gene-8.png and b/reference/vis_gene-8.png differ
diff --git a/reference/vis_gene-9.png b/reference/vis_gene-9.png
index 9123b986..fa2c6a94 100644
Binary files a/reference/vis_gene-9.png and b/reference/vis_gene-9.png differ
diff --git a/reference/vis_gene.html b/reference/vis_gene.html
index e39667fc..f0e49f68 100644
--- a/reference/vis_gene.html
+++ b/reference/vis_gene.html
@@ -66,7 +66,7 @@
@@ -220,12 +220,12 @@ Value
Details
This function subsets spe to the given sample and prepares the
-data and title for vis_gene_p(). It also adds a caption to the plot.
+data and title for vis_gene_p(). It also adds a caption to the plot.
See also
Other Spatial gene visualization functions:
-vis_gene_p(),
+vis_gene_p(),
vis_grid_gene()
@@ -341,8 +341,7 @@ Examples
)
print(p8)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:22.728238 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:48.10019 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene_p-1.png b/reference/vis_gene_p-1.png
new file mode 100644
index 00000000..24287b46
Binary files /dev/null and b/reference/vis_gene_p-1.png differ
diff --git a/reference/vis_gene_p.html b/reference/vis_gene_p.html
new file mode 100644
index 00000000..4f32d6a8
--- /dev/null
+++ b/reference/vis_gene_p.html
@@ -0,0 +1,245 @@
+
+Sample spatial gene visualization workhorse function — vis_gene_p • spatialLIBD
+
+
+
+
+
+
+
+
+
+
+
+
+ This function visualizes the gene expression stored in assays(spe) or any
+continuous variable stored in colData(spe) for one given sample at the
+spot-level using (by default) the histology information on the background.
+This is the function that does all the plotting behind vis_gene()
+To visualize clusters (or any discrete variable) use vis_clus_p().
+
+
+
+ vis_gene_p(
+ spe,
+ d,
+ sampleid = unique(spe$sample_id)[1],
+ spatial,
+ title,
+ viridis = TRUE,
+ image_id = "lowres",
+ alpha = NA,
+ cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4",
+ "springgreen", "goldenrod", "red"),
+ point_size = 2,
+ auto_crop = TRUE,
+ na_color = "#CCCCCC40",
+ legend_title = ""
+)
+
+
+
+ Arguments
+
+
+- spe
+A
+SpatialExperiment-class
+object. See fetch_data() for how to download some example objects or
+read10xVisiumWrapper() to read in spaceranger --count output files and
+build your own spe object.
- d
+A data.frame() with the sample-level information. This is
+typically obtained using cbind(colData(spe), spatialCoords(spe)).
+The data.frame has to contain
+a column with the continuous variable data to plot stored under d$COUNT.
- sampleid
+A character(1) specifying which sample to plot from
+colData(spe)$sample_id (formerly colData(spe)$sample_name).
- spatial
+A logical(1) indicating whether to include the histology
+layer from geom_spatial(). If you plan to use
+ggplotly() then it's best to set this to FALSE.
- title
+The title for the plot.
- viridis
+A logical(1) whether to use the color-blind friendly
+palette from viridis or the color palette used
+in the paper that was chosen for contrast when visualizing the data on
+top of the histology image. One issue is being able to differentiate low
+values from NA ones due to the purple-ish histology information that is
+dependent on cell density.
- image_id
+A character(1) with the name of the image ID you want to
+use in the background.
- alpha
+A numeric(1) in the [0, 1] range that specifies the
+transparency level of the data on the spots.
- cont_colors
+A character() vector of colors that supersedes the
+viridis argument.
- point_size
+A numeric(1) specifying the size of the points. Defaults
+to 1.25. Some colors look better if you use 2 for instance.
- auto_crop
+A logical(1) indicating whether to automatically crop
+the image / plotting area, which is useful if the Visium capture area is
+not centered on the image and if the image is not a square.
- na_color
+A character(1) specifying a color for the NA values.
+If you set alpha = NA then it's best to set na_color to a color that has
+alpha blending already, which will make non-NA values pop up more and the NA
+values will show with a lighter color. This behavior is lost when alpha is
+set to a non-NA value.
- legend_title
+A character(1) specifying the legend title.
+
+ Value
+ A ggplot2 object.
+
+
+ See also
+ Other Spatial gene visualization functions:
+vis_gene(),
+vis_grid_gene()
+
+
+
+ Examples
+
+if (enough_ram()) {
+ ## Obtain the necessary data
+ if (!exists("spe")) spe <- fetch_data("spe")
+
+ ## Prepare the data for the plotting function
+ spe_sub <- spe[, spe$sample_id == "151673"]
+ df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
+ df$COUNT <- df$expr_chrM_ratio
+
+ ## Don't plot the histology information
+ p <- vis_gene_p(
+ spe = spe_sub,
+ d = df,
+ sampleid = "151673",
+ title = "151673 chrM expr ratio",
+ spatial = FALSE
+ )
+ print(p)
+
+ ## Clean up
+ rm(spe_sub)
+}
+#> 2024-07-17 13:53:14.003193 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/reference/vis_grid_clus-1.png b/reference/vis_grid_clus-1.png
index fc3c2d6c..ea564e20 100644
Binary files a/reference/vis_grid_clus-1.png and b/reference/vis_grid_clus-1.png differ
diff --git a/reference/vis_grid_clus.html b/reference/vis_grid_clus.html
index beb4cdd7..a1aec073 100644
--- a/reference/vis_grid_clus.html
+++ b/reference/vis_grid_clus.html
@@ -65,7 +65,7 @@
Sample spatial cluster visualization grid
- Source: R/vis_grid_clus.R
+ Source: R/vis_grid_clus.R
vis_grid_clus.Rd
@@ -237,8 +237,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:41.57373 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:29.053452 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_grid_gene-1.png b/reference/vis_grid_gene-1.png
index d8f795d8..b246fec3 100644
Binary files a/reference/vis_grid_gene-1.png and b/reference/vis_grid_gene-1.png differ
diff --git a/reference/vis_grid_gene.html b/reference/vis_grid_gene.html
index f5428110..7f5c56b0 100644
--- a/reference/vis_grid_gene.html
+++ b/reference/vis_grid_gene.html
@@ -66,7 +66,7 @@
Sample spatial gene visualization grid
- Source: R/vis_grid_gene.R
+ Source: R/vis_grid_gene.R
vis_grid_gene.Rd
@@ -234,7 +234,7 @@ Details
See also
Other Spatial gene visualization functions:
vis_gene(),
-vis_gene_p()
+vis_gene_p()
@@ -256,8 +256,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:53.38865 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:45.486537 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/sitemap.xml b/sitemap.xml
index d4f77066..8a33c15f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -62,6 +62,7 @@
/reference/vis_clus.html /reference/vis_clus_p.html /reference/vis_gene.html /reference/vis_gene_p.html /reference/vis_grid_clus.html /reference/vis_grid_gene.html
From Gencode## Show the GTF cache location
gtf_cache
-#> BFC23
-#> "/Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/100014a479f08_gencode.v32.annotation.gtf.gz"
+#> BFC4
+#> "/github/home/.cache/R/BiocFileCache/49832febaac_gencode.v32.annotation.gtf.gz"
## Import into R (takes ~1 min)
gtf <- rtracklayer::import(gtf_cache)
@@ -794,7 +792,7 @@ Run the interactive website## Locate our documentation files
docs_path <- system.file("app", "www", package = "spatialLIBD")
docs_path
-#> [1] "/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/spatialLIBD/app/www"
+#> [1] "/__w/_temp/Library/spatialLIBD/app/www"
list.files(docs_path)
#> [1] "documentation_sce_layer.md" "documentation_spe.md"
#> [3] "favicon.ico" "footer.html"
@@ -820,11 +818,11 @@ Wrapper functions= c("lowres", "hires", "detected", "aligned"), load = TRUE,
reference_gtf = gtf_cache
)
-#> 2024-07-16 17:06:02.30044 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
-#> 2024-07-16 17:06:10.20779 read10xVisiumAnalysis: reading analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.42459 add10xVisiumAnalysis: adding analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.61105 rtracklayer::import: reading the reference GTF file
-#> 2024-07-16 17:06:31.708652 adding gene information to the SPE object
+#> 2024-07-17 13:57:08.168846 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
+#> 2024-07-17 13:57:19.596362 read10xVisiumAnalysis: reading analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.702059 add10xVisiumAnalysis: adding analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.945565 rtracklayer::import: reading the reference GTF file
+#> 2024-07-17 13:57:47.519521 adding gene information to the SPE object
#> Warning: Gene IDs did not match. This typically happens when you are not using
#> the same GTF file as the one that was used by SpaceRanger. For example, one
#> file uses GENCODE IDs and the other one ENSEMBL IDs. read10xVisiumWrapper()
@@ -832,7 +830,7 @@ Wrapper functions#> Warning: Dropping 29 out of 36601 genes for which we don't have information on
#> the reference GTF file. This typically happens when you are not using the same
#> GTF file as the one that was used by SpaceRanger.
-#> 2024-07-16 17:06:31.907411 adding information used by spatialLIBD
+#> 2024-07-17 13:57:47.776325 adding information used by spatialLIBD
## Run our shiny app
if (interactive()) {
@@ -1116,200 +1114,202 @@ Reproducibilitylibrary("knitr")
knit("TenX_data_download.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:06:32 EDT"
+#> [1] "2024-07-17 13:57:48 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 1.183 mins
+#> Time difference of 1.705 mins
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────
-#> package * version date (UTC) lib source
-#> abind 1.4-5 2016-07-21 [1] CRAN (R 4.4.0)
-#> AnnotationDbi 1.66.0 2024-05-01 [1] Bioconductor 3.19 (R 4.4.0)
-#> AnnotationHub 3.12.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.0)
-#> attempt 0.3.1 2020-05-03 [1] CRAN (R 4.4.0)
-#> backports 1.5.0 2024-05-23 [1] CRAN (R 4.4.0)
-#> beachmat 2.20.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.0)
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#>
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+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
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@@ -1356,8 +1356,10 @@ Bibliography[5]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[6]
@@ -1385,13 +1387,16 @@ Bibliography[9]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[10]
H. Wickham. lobstr: Visualize R Data Structures with Trees. R
-package version 1.1.2. 2022. URL:
-https://CRAN.R-project.org/package=lobstr.
+package version 1.1.2, https://github.com/r-lib/lobstr. 2022. URL:
+https://lobstr.r-lib.org/.
[11]
@@ -1402,8 +1407,8 @@ Bibliography[12]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[13]
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png
index befc0397..681004b2 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png differ
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png
index 017fcd18..ac8b5fff 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png differ
diff --git a/articles/guide_to_spatial_registration.html b/articles/guide_to_spatial_registration.html
index a056ae9f..cb254465 100644
--- a/articles/guide_to_spatial_registration.html
+++ b/articles/guide_to_spatial_registration.html
@@ -101,9 +101,9 @@ Louise
Development
lahuuki@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/guide_to_spatial_registration.Rmd
+ Source: vignettes/guide_to_spatial_registration.Rmd
guide_to_spatial_registration.Rmd
@@ -268,8 +268,6 @@ Load required packages
library("spatialLIBD")
-#> Warning: package 'S4Vectors' was built under R version 4.4.1
-#> Warning: package 'IRanges' was built under R version 4.4.1
library("SingleCellExperiment")
@@ -290,7 +288,7 @@ Spatial Reference
## get reference layer enrichment statistics
layer_modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:13.829724 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:54:13.294755 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
layer_modeling_results$enrichment[1:5, 1:5]
#> t_stat_WM t_stat_Layer1 t_stat_Layer2 t_stat_Layer3 t_stat_Layer4
@@ -393,18 +391,18 @@ Get Enrichment statistics
gene_ensembl = "gene_id",
gene_name = "gene_name"
)
-#> 2024-07-16 17:04:17.342908 make pseudobulk object
-#> 2024-07-16 17:04:18.696265 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:04:18.724833 drop lowly expressed genes
-#> 2024-07-16 17:04:18.799779 normalize expression
-#> 2024-07-16 17:04:19.584255 create model matrix
-#> 2024-07-16 17:04:19.595618 run duplicateCorrelation()
-#> 2024-07-16 17:04:25.229344 The estimated correlation is: 0.138734774807097
-#> 2024-07-16 17:04:25.231011 computing enrichment statistics
-#> 2024-07-16 17:04:25.960375 extract and reformat enrichment results
-#> 2024-07-16 17:04:26.003855 running the baseline pairwise model
-#> 2024-07-16 17:04:26.12952 computing pairwise statistics
-#> 2024-07-16 17:04:27.403954 computing F-statistics
+#> 2024-07-17 13:54:21.031386 make pseudobulk object
+#> 2024-07-17 13:54:22.727446 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:54:22.789323 drop lowly expressed genes
+#> 2024-07-17 13:54:22.963372 normalize expression
+#> 2024-07-17 13:54:24.427132 create model matrix
+#> 2024-07-17 13:54:24.451001 run duplicateCorrelation()
+#> 2024-07-17 13:54:37.623842 The estimated correlation is: 0.138734774807097
+#> 2024-07-17 13:54:37.626295 computing enrichment statistics
+#> 2024-07-17 13:54:38.79442 extract and reformat enrichment results
+#> 2024-07-17 13:54:38.851417 running the baseline pairwise model
+#> 2024-07-17 13:54:39.041435 computing pairwise statistics
+#> 2024-07-17 13:54:40.421524 computing F-statistics
Extract Enrichment t-statistics
@@ -564,187 +562,189 @@ Reproducibilitylibrary("knitr")
knit("guide_to_spatial_registration.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:28 EDT"
+#> [1] "2024-07-17 13:54:41 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.924 secs
+#> Time difference of 40.965 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -782,8 +782,10 @@ Bibliography[4]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[5]
@@ -817,8 +819,8 @@ Bibliography[9]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[10]
diff --git a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png
index 37955c4b..d3a2dbfd 100644
Binary files a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png and b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png differ
diff --git a/articles/multi_gene_plots.html b/articles/multi_gene_plots.html
index 684a2bbb..847ca6a7 100644
--- a/articles/multi_gene_plots.html
+++ b/articles/multi_gene_plots.html
@@ -108,9 +108,9 @@ Leonardo
Public Health
lcolladotor@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/multi_gene_plots.Rmd
+ Source: vignettes/multi_gene_plots.Rmd
multi_gene_plots.Rmd
@@ -195,9 +195,9 @@ Plotting One Gene
modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:43.021669 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:06.762958 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
sce_layer <- fetch_data(type = "sce_layer")
-#> 2024-07-16 17:04:43.645201 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:07.675711 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
sig_genes <- sig_genes_extract_all(
n = 400,
modeling_results = modeling_results,
@@ -421,189 +421,191 @@ Reproducibilitylibrary("knitr")
knit("multi_gene_plots.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:53 EDT"
+#> [1] "2024-07-17 13:55:23 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.564 secs
+#> Time difference of 36.887 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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diff --git a/articles/spatialLIBD.html b/articles/spatialLIBD.html
index 241db4f0..3e707196 100644
--- a/articles/spatialLIBD.html
+++ b/articles/spatialLIBD.html
@@ -114,9 +114,9 @@ Andrew E.
Campus
andrew.jaffe@libd.org
- 16 July 2024
+ 17 July 2024
- Source: vignettes/spatialLIBD.Rmd
+ Source: vignettes/spatialLIBD.Rmd
spatialLIBD.Rmd
@@ -414,7 +414,7 @@ Downloading the data with s
## Download the small example sce data
sce <- fetch_data(type = "sce_example", eh = ehub)
-#> 2024-07-16 17:05:03.908351 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:39.830372 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
## Convert to a SpatialExperiment object
spe <- sce_to_spe(sce)
@@ -426,9 +426,9 @@ Downloading the data with s
## Query ExperimentHub and download the data
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer", eh = ehub)
-#> 2024-07-16 17:05:07.931392 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.107964 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
modeling_results <- fetch_data("modeling_results", eh = ehub)
-#> 2024-07-16 17:05:08.248131 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.559624 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
Once you have downloaded the objects, we can explore them a little
bit
@@ -501,7 +501,7 @@ Downloading the data with s
)
)
#> user system elapsed
-#> 5.090 0.218 5.325
+#> 9.944 0.296 10.247
## Explore the result
class(sig_genes)
@@ -707,7 +707,7 @@ Spot-level genes and continuo
the histology set of purple tones that are noticeable when the
continuous variable is below or equal to the minCount (in
our palettes such points have a 'transparent' color). For
-more details, check the internal code of vis_gene_p().
+more details, check the internal code of vis_gene_p().
Extract significant genes
@@ -1018,7 +1018,7 @@ SpatialExperiment support
As of version 1.3.3, spatialLIBD
supports the SpatialExperiment class from SpatialExperiment.
-The functions vis_gene_p(), vis_gene(),
+The functions vis_gene_p(), vis_gene(),
vis_grid_clus(), vis_grid_gene(),
vis_clus(), vis_clus_p(),
geom_spatial() now work with SpatialExperiment
@@ -1108,7 +1108,7 @@
Generating our data (legacy)vis_clus_p() and
-vis_gene_p(). Having the data from all images in a single
+vis_gene_p(). Having the data from all images in a single
object allows you to use the spot-level data from all images to compute
clusters and do other similar analyses to the ones you would do with
sc/snRNA-seq data. The script creates the
@@ -1377,189 +1377,191 @@ Reproducibilitylibrary("knitr")
knit("spatialLIBD.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:05:18 EDT"
+#> [1] "2024-07-17 13:56:02 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 22.031 secs
+#> Time difference of 34.974 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
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+#> shinyWidgets 0.8.6 2024-04-24 [1] RSPM (R 4.4.0)
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+#> spam 2.10-0 2023-10-23 [1] RSPM (R 4.4.0)
+#> SparseArray 1.4.8 2024-05-24 [1] Bioconductor 3.19 (R 4.4.1)
+#> sparseMatrixStats 1.16.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
+#> SpatialExperiment * 1.14.0 2024-05-01 [1] Bioconductor 3.19 (R 4.4.1)
+#> spatialLIBD * 1.17.6 2024-07-17 [1] Bioconductor
+#> statmod 1.5.0 2023-01-06 [1] RSPM (R 4.4.0)
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+#> stringr 1.5.1 2023-11-14 [2] RSPM (R 4.4.0)
+#> SummarizedExperiment * 1.34.0 2024-05-01 [1] Bioconductor 3.19 (R 4.4.1)
+#> systemfonts 1.1.0 2024-05-15 [2] RSPM (R 4.4.0)
+#> textshaping 0.4.0 2024-05-24 [2] RSPM (R 4.4.0)
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+#> withr 3.0.0 2024-01-16 [2] RSPM (R 4.4.0)
+#> xfun 0.45 2024-06-16 [2] RSPM (R 4.4.0)
+#> XML 3.99-0.17 2024-06-25 [1] RSPM (R 4.4.0)
+#> xml2 1.3.6 2023-12-04 [2] RSPM (R 4.4.0)
+#> xtable 1.8-4 2019-04-21 [2] RSPM (R 4.4.0)
+#> XVector 0.44.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
+#> yaml 2.3.9 2024-07-05 [2] RSPM (R 4.4.0)
+#> zlibbioc 1.50.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -1594,8 +1596,8 @@ Bibliography[4]
W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application
-Framework for R. R package version 1.8.1.1. 2024. URL:
-https://CRAN.R-project.org/package=shiny.
+Framework for R. R package version 1.8.1.1, https://github.com/rstudio/shiny. 2024. URL:
+https://shiny.posit.co/.
[5]
@@ -1616,7 +1618,7 @@ Bibliography[7]
C. Fay, V. Guyader, S. Rochette, et al. golem: A Framework for
Robust Shiny Applications. R package version 0.4.1. 2023. URL:
-https://CRAN.R-project.org/package=golem.
+https://github.com/ThinkR-open/golem.
[8]
@@ -1630,7 +1632,7 @@ Bibliography[9]
C. Gillespie. benchmarkme: Crowd Sourced System Benchmarks. R
package version 1.0.8. 2022. URL:
-https://CRAN.R-project.org/package=benchmarkme.
+https://github.com/csgillespie/benchmarkme.
[10]
@@ -1718,42 +1720,53 @@ Bibliography[20]
M. Morgan, V. Obenchain, J. Hester, et al. SummarizedExperiment:
SummarizedExperiment container. R package version 1.34.0. 2024.
+DOI:
+10.18129/B9.bioc.SummarizedExperiment.
URL:
https://bioconductor.org/packages/SummarizedExperiment.
[21]
M. Morgan and L. Shepherd. AnnotationHub: Client to access
-AnnotationHub resources. R package version 3.12.0. 2024.
+AnnotationHub resources. R package version 3.12.0. 2024. DOI:
+10.18129/B9.bioc.AnnotationHub.
+URL:
+https://bioconductor.org/packages/AnnotationHub.
[22]
M. Morgan and L. Shepherd. ExperimentHub: Client to access
-ExperimentHub resources. R package version 2.12.0. 2024.
+ExperimentHub resources. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.ExperimentHub.
+URL:
+https://bioconductor.org/packages/ExperimentHub.
[23]
E. Neuwirth. RColorBrewer: ColorBrewer Palettes. R package
-version 1.1-3. 2022. URL:
-https://CRAN.R-project.org/package=RColorBrewer.
+version 1.1-3. 2022.
[24]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[25]
J. Ooms. magick: Advanced Graphics and Image-Processing in R. R
-package version 2.8.3. 2024. URL:
-https://CRAN.R-project.org/package=magick.
+package version 2.8.4. 2024. URL:
+https://docs.ropensci.org/magick/https://ropensci.r-universe.dev/magick.
[26]
H. Pagès, M. Lawrence, and P. Aboyoun. S4Vectors: Foundation of
vector-like and list-like containers in Bioconductor. R package
-version 0.42.1. 2024. URL:
+version 0.42.1. 2024. DOI:
+10.18129/B9.bioc.S4Vectors.
+URL:
https://bioconductor.org/packages/S4Vectors.
@@ -1789,7 +1802,10 @@
Bibliography[31]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[32]
@@ -1812,14 +1828,14 @@ Bibliography[35]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[36]
C. Wilke. cowplot: Streamlined Plot Theme and Plot Annotations for
‘ggplot2’. R package version 1.1.3. 2024. URL:
-https://CRAN.R-project.org/package=cowplot.
+https://wilkelab.org/cowplot/.
[37]
@@ -1832,7 +1848,7 @@ Bibliography[38]
Y. Xie, J. Cheng, and X. Tan. DT: A Wrapper of the JavaScript
Library ‘DataTables’. R package version 0.33. 2024. URL:
-https://CRAN.R-project.org/package=DT.
+https://github.com/rstudio/DT.
diff --git a/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png b/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png
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diff --git a/articles/spatialLIBD_files/figure-html/vis_gene-2.png b/articles/spatialLIBD_files/figure-html/vis_gene-2.png
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diff --git a/articles/spatialLIBD_files/figure-html/vis_gene-3.png b/articles/spatialLIBD_files/figure-html/vis_gene-3.png
index 5becf124..9c87ad47 100644
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diff --git a/authors.html b/authors.html
index 3d9fe61e..5953cb2d 100644
--- a/authors.html
+++ b/authors.html
@@ -107,7 +107,7 @@ Authors and Citation
diff --git a/news/index.html b/news/index.html
index 38fa2bfe..93a36916 100644
--- a/news/index.html
+++ b/news/index.html
@@ -63,7 +63,7 @@
@@ -221,7 +221,7 @@ spatialLIBD
-
run_app() now offers the option to chose any of the paletteer::paletteer_d color palettes for discrete variables.
-
-
Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
+Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
-
run_app() now looks for columns that end with ’_colors’ in their name which can be used to pre-specify colors for any companion variables. For example if you have spe$my_groups and spe$my_groups_colors then the second one can specify the colors that will be used for visualizing spe$my_groups. This makes specifying default colors more flexible than before, and the user is still free to change them if necessary.
@@ -265,7 +265,7 @@ spatialLIBD 1
spatialLIBD 1.7.6
NEW FEATURES
-
-
vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
+vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
- The shiny app now has an input controlling the point size. If you increase it to say
5, then if you zoom in the clusters (interactive) panel, you can see larger spots when zooming in.
- These features are related to https://github.com/LieberInstitute/spatialLIBD/issues/28 although the spot diameter is still not the true spot diameter. However, now you have more flexibility for visualizing the spots.
@@ -333,7 +333,7 @@ spatialLIBD
spatialLIBD 1.3.3
NEW FEATURES
-- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
+- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
- Updated citation information to reflect that https://doi.org/10.1038/s41593-020-00787-0 is now public. Also added a link on the README to https://doi.org/10.6084/m9.figshare.13623902.v1 for the manuscript high resolution images.
diff --git a/pkgdown.yml b/pkgdown.yml
index 46fd2df0..f01eec79 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,4 +6,4 @@ articles:
multi_gene_plots: multi_gene_plots.html
spatialLIBD: spatialLIBD.html
TenX_data_download: TenX_data_download.html
-last_built: 2024-07-16T21:00Z
+last_built: 2024-07-17T13:48Z
diff --git a/reference/Rplot001.png b/reference/Rplot001.png
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diff --git a/reference/add10xVisiumAnalysis.html b/reference/add10xVisiumAnalysis.html
index da55e67a..6dd8b9b8 100644
--- a/reference/add10xVisiumAnalysis.html
+++ b/reference/add10xVisiumAnalysis.html
@@ -65,7 +65,7 @@
Add analysis data from a 10x Genomics Visium experiment to a SPE object
- Source: R/add10xVisiumAnalysis.R
+ Source: R/add10xVisiumAnalysis.R
add10xVisiumAnalysis.Rd
@@ -120,7 +120,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/add_images.html b/reference/add_images.html
index 37749b90..db2faadf 100644
--- a/reference/add_images.html
+++ b/reference/add_images.html
@@ -71,7 +71,7 @@
Add non-standard images with the same dimensions as current ones
- Source: R/add_images.R
+ Source: R/add_images.R
add_images.Rd
@@ -165,30 +165,29 @@ Examples
image_paths = c("151507" = "https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151507_tissue_lowres_image.png")
))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:18.72371 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
-#> 2024-07-16 17:00:29.794628 adding image for sample 151507
-#> 2024-07-16 17:00:30.766353 adding image for sample 151508
+#> 2024-07-17 13:48:26.600477 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:41.90188 adding image for sample 151507
+#> 2024-07-17 13:48:42.538745 adding image for sample 151508
#> Warning: No image was found for sample: 151508
-#> 2024-07-16 17:00:30.766579 adding image for sample 151509
+#> 2024-07-17 13:48:42.539054 adding image for sample 151509
#> Warning: No image was found for sample: 151509
-#> 2024-07-16 17:00:30.766725 adding image for sample 151510
+#> 2024-07-17 13:48:42.539261 adding image for sample 151510
#> Warning: No image was found for sample: 151510
-#> 2024-07-16 17:00:30.766858 adding image for sample 151669
+#> 2024-07-17 13:48:42.539459 adding image for sample 151669
#> Warning: No image was found for sample: 151669
-#> 2024-07-16 17:00:30.76698 adding image for sample 151670
+#> 2024-07-17 13:48:42.539652 adding image for sample 151670
#> Warning: No image was found for sample: 151670
-#> 2024-07-16 17:00:30.767101 adding image for sample 151671
+#> 2024-07-17 13:48:42.539843 adding image for sample 151671
#> Warning: No image was found for sample: 151671
-#> 2024-07-16 17:00:30.767222 adding image for sample 151672
+#> 2024-07-17 13:48:42.540033 adding image for sample 151672
#> Warning: No image was found for sample: 151672
-#> 2024-07-16 17:00:30.76734 adding image for sample 151673
+#> 2024-07-17 13:48:42.540223 adding image for sample 151673
#> Warning: No image was found for sample: 151673
-#> 2024-07-16 17:00:30.767458 adding image for sample 151674
+#> 2024-07-17 13:48:42.540414 adding image for sample 151674
#> Warning: No image was found for sample: 151674
-#> 2024-07-16 17:00:30.767576 adding image for sample 151675
+#> 2024-07-17 13:48:42.540604 adding image for sample 151675
#> Warning: No image was found for sample: 151675
-#> 2024-07-16 17:00:30.767696 adding image for sample 151676
+#> 2024-07-17 13:48:42.540791 adding image for sample 151676
#> Warning: No image was found for sample: 151676
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
diff --git a/reference/add_key.html b/reference/add_key.html
index 7dce6d11..220b5ded 100644
--- a/reference/add_key.html
+++ b/reference/add_key.html
@@ -65,7 +65,7 @@
@@ -124,8 +124,7 @@ Examples
spe$key_original <- NULL
head(spe$key)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:33.017537 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:44.910936 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> [1] "151507_AAACAACGAATAGTTC-1" "151507_AAACAAGTATCTCCCA-1"
#> [3] "151507_AAACAATCTACTAGCA-1" "151507_AAACACCAATAACTGC-1"
#> [5] "151507_AAACAGCTTTCAGAAG-1" "151507_AAACAGGGTCTATATT-1"
diff --git a/reference/add_qc_metrics-1.png b/reference/add_qc_metrics-1.png
index cade42d4..2e65d510 100644
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diff --git a/reference/add_qc_metrics-3.png b/reference/add_qc_metrics-3.png
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diff --git a/reference/add_qc_metrics-4.png b/reference/add_qc_metrics-4.png
index cd287d06..39a4439a 100644
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diff --git a/reference/add_qc_metrics-5.png b/reference/add_qc_metrics-5.png
index e6624e22..e1b6345a 100644
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diff --git a/reference/add_qc_metrics-6.png b/reference/add_qc_metrics-6.png
index 95168130..70357959 100644
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diff --git a/reference/add_qc_metrics-7.png b/reference/add_qc_metrics-7.png
index b21b0b71..0a06596e 100644
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diff --git a/reference/add_qc_metrics-8.png b/reference/add_qc_metrics-8.png
index 41ab0f4e..24a2c0e0 100644
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diff --git a/reference/add_qc_metrics.html b/reference/add_qc_metrics.html
index db6a4d92..9c72a786 100644
--- a/reference/add_qc_metrics.html
+++ b/reference/add_qc_metrics.html
@@ -67,7 +67,7 @@
Quality Control for Spatial Data
- Source: R/add_qc_metrics.R
+ Source: R/add_qc_metrics.R
add_qc_metrics.Rd
@@ -144,8 +144,7 @@ Author
Examples
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:43.634355 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f563a40ecf7_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
+#> 2024-07-17 13:49:00.582195 loading file /github/home/.cache/R/BiocFileCache/49872dc0d45_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
diff --git a/reference/annotate_registered_clusters.html b/reference/annotate_registered_clusters.html
index fd6421d6..50b43af5 100644
--- a/reference/annotate_registered_clusters.html
+++ b/reference/annotate_registered_clusters.html
@@ -67,7 +67,7 @@
Annotated spatially-registered clusters
- Source: R/annotate_registered_clusters.R
+ Source: R/annotate_registered_clusters.R
annotate_registered_clusters.Rd
@@ -137,8 +137,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:51.762523 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:13.326528 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/check_modeling_results.html b/reference/check_modeling_results.html
index e56f7419..f95254df 100644
--- a/reference/check_modeling_results.html
+++ b/reference/check_modeling_results.html
@@ -64,7 +64,7 @@
Check input modeling_results
- Source: R/check_modeling_results.R
+ Source: R/check_modeling_results.R
check_modeling_results.Rd
@@ -108,8 +108,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:52.678188 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:14.441658 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Check the object
xx <- check_modeling_results(modeling_results)
diff --git a/reference/check_sce.html b/reference/check_sce.html
index 8a937cdf..fdc02746 100644
--- a/reference/check_sce.html
+++ b/reference/check_sce.html
@@ -66,7 +66,7 @@
@@ -131,8 +131,7 @@ Examples
## Check the object
check_sce(sce_example)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:53.63802 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:15.651297 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
#> class: SingleCellExperiment
#> dim: 33538 47681
#> metadata(1): image
diff --git a/reference/check_sce_layer.html b/reference/check_sce_layer.html
index e6129283..c926c5cf 100644
--- a/reference/check_sce_layer.html
+++ b/reference/check_sce_layer.html
@@ -64,7 +64,7 @@
Check input sce_layer
- Source: R/check_sce_layer.R
+ Source: R/check_sce_layer.R
check_sce_layer.Rd
@@ -112,8 +112,7 @@ Examples
## Obtain example data from the HumanPilot project
## (Maynard, Collado-Torres, et al, 2021)
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:55.536908 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:18.090538 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Check the pseudo-bulked data
check_sce_layer(sce_layer)
diff --git a/reference/check_spe.html b/reference/check_spe.html
index 00f18aab..262e37d5 100644
--- a/reference/check_spe.html
+++ b/reference/check_spe.html
@@ -64,7 +64,7 @@
@@ -123,8 +123,7 @@ Examples
## Check the object
check_spe(spe)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:56.493054 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:19.444343 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> class: SpatialExperiment
#> dim: 33538 47681
#> metadata(0):
diff --git a/reference/cluster_export.html b/reference/cluster_export.html
index 576e5969..41dcf6be 100644
--- a/reference/cluster_export.html
+++ b/reference/cluster_export.html
@@ -67,7 +67,7 @@
Export a column with cluster results
- Source: R/cluster_export.R
+ Source: R/cluster_export.R
cluster_export.Rd
@@ -134,8 +134,7 @@ Examples
cluster_export(spe, "spatialLIBD")
cluster_export(spe, "GraphBased")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:06.836252 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:34.076008 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
diff --git a/reference/cluster_import.html b/reference/cluster_import.html
index feed9a97..585bc91f 100644
--- a/reference/cluster_import.html
+++ b/reference/cluster_import.html
@@ -66,7 +66,7 @@
@@ -137,12 +137,11 @@ Examples
## Re-import them
colData(cluster_import(spe))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:17.501482 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:49.230922 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/spatialLIBD' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/spatialLIBD' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/GraphBased' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/GraphBased' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> DataFrame with 47681 rows and 71 columns
#> key sample_id Cluster sum_umi
diff --git a/reference/enough_ram.html b/reference/enough_ram.html
index 1aefe5c0..17fada89 100644
--- a/reference/enough_ram.html
+++ b/reference/enough_ram.html
@@ -63,7 +63,7 @@
Determine if you have enough RAM memory
- Source: R/enough_ram.R
+ Source: R/enough_ram.R
enough_ram.Rd
diff --git a/reference/fetch_data.html b/reference/fetch_data.html
index 860fcc8a..626b28ea 100644
--- a/reference/fetch_data.html
+++ b/reference/fetch_data.html
@@ -71,7 +71,7 @@
Download the Human DLPFC Visium data from LIBD
- Source: R/fetch_data.R
+ Source: R/fetch_data.R
fetch_data.Rd
@@ -166,8 +166,7 @@ Examples
## Download the SingleCellExperiment object
## at the layer-level
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:28.986594 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:04.599487 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Explore the data
sce_layer
diff --git a/reference/frame_limits.html b/reference/frame_limits.html
index 0a945d2b..ce67964f 100644
--- a/reference/frame_limits.html
+++ b/reference/frame_limits.html
@@ -73,7 +73,7 @@
@@ -154,8 +154,7 @@ Examples
## Obtain the frame limits for one sample
frame_limits(spe, sampleid = "151673")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:30.408348 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:07.106212 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> $y_min
#> [1] 64
#>
diff --git a/reference/gene_set_enrichment.html b/reference/gene_set_enrichment.html
index 58358fa3..69f114cc 100644
--- a/reference/gene_set_enrichment.html
+++ b/reference/gene_set_enrichment.html
@@ -68,7 +68,7 @@
Evaluate the enrichment for a list of gene sets
- Source: R/gene_set_enrichment.R
+ Source: R/gene_set_enrichment.R
gene_set_enrichment.Rd
@@ -176,8 +176,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:40.855511 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:21.075222 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/gene_set_enrichment_plot-1.png b/reference/gene_set_enrichment_plot-1.png
index d68b19ec..d366f433 100644
Binary files a/reference/gene_set_enrichment_plot-1.png and b/reference/gene_set_enrichment_plot-1.png differ
diff --git a/reference/gene_set_enrichment_plot-2.png b/reference/gene_set_enrichment_plot-2.png
index 78df31f0..dbc691ef 100644
Binary files a/reference/gene_set_enrichment_plot-2.png and b/reference/gene_set_enrichment_plot-2.png differ
diff --git a/reference/gene_set_enrichment_plot.html b/reference/gene_set_enrichment_plot.html
index 40392d13..ffdc11f2 100644
--- a/reference/gene_set_enrichment_plot.html
+++ b/reference/gene_set_enrichment_plot.html
@@ -64,7 +64,7 @@
Plot the gene set enrichment results
- Source: R/gene_set_enrichment_plot.R
+ Source: R/gene_set_enrichment_plot.R
gene_set_enrichment_plot.Rd
@@ -178,8 +178,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:41.867526 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:22.531835 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/geom_spatial-1.png b/reference/geom_spatial-1.png
index 64fd3d7a..946c446a 100644
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diff --git a/reference/geom_spatial.html b/reference/geom_spatial.html
index 5d50b49e..42e5c07c 100644
--- a/reference/geom_spatial.html
+++ b/reference/geom_spatial.html
@@ -66,7 +66,7 @@
A ggplot2 layer for visualizing the Visium histology
- Source: R/geom_spatial.R
+ Source: R/geom_spatial.R
geom_spatial.Rd
@@ -74,7 +74,7 @@ A ggplot2 layer for visualizing the Visium histology
This function defines a ggplot2::layer() for visualizing the histology
image from Visium. It can be combined with other ggplot2 functions for
visualizing the clusters as in vis_clus_p() or gene-level information
-as in vis_gene_p().
+as in vis_gene_p().
@@ -175,8 +175,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:43.207432 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:24.396394 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/get_colors.html b/reference/get_colors.html
index e49a44bf..dfbeb5c2 100644
--- a/reference/get_colors.html
+++ b/reference/get_colors.html
@@ -64,7 +64,7 @@
Obtain the colors for a set of cluster names
- Source: R/get_colors.R
+ Source: R/get_colors.R
get_colors.Rd
@@ -84,7 +84,7 @@ Arguments
- colors
A vector of colors. If NULL then a set of default colors will
be used when clusters has less than 12 unique values, otherwise
-Polychrome::palette36 will be used which can
+Polychrome::palette36 will be used which can
generate up to 36 unique colors. If the number of unique clusters is beyond
36 then this function will fail.
Examples
## Obtain the necessary data
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:54.433623 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:39.853193 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Example layer colors with the corresponding names
get_colors(libd_layer_colors, sce_layer$layer_guess)
diff --git a/reference/img_edit-1.png b/reference/img_edit-1.png
index 94154fc3..9af3f312 100644
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diff --git a/reference/img_edit.html b/reference/img_edit.html
index 9df344ec..004b6d82 100644
--- a/reference/img_edit.html
+++ b/reference/img_edit.html
@@ -65,7 +65,7 @@
@@ -222,8 +222,7 @@ Examples
x <- img_edit(spe, sampleid = "151507", brightness = 25)
plot(x)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:56.683064 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:41.084926 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/img_update.html b/reference/img_update.html
index 5b6a0f39..5d92fe1f 100644
--- a/reference/img_update.html
+++ b/reference/img_update.html
@@ -63,7 +63,7 @@
@@ -139,8 +139,7 @@ Examples
## Reduce brightness to 25% and update the imgData()
imgData(img_update(spe, sampleid = "151507", brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:07.614049 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:56.77859 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/img_update_all.html b/reference/img_update_all.html
index e322e40f..8a0c7996 100644
--- a/reference/img_update_all.html
+++ b/reference/img_update_all.html
@@ -65,7 +65,7 @@
Update the images for all samples
- Source: R/img_update_all.R
+ Source: R/img_update_all.R
img_update_all.Rd
@@ -138,8 +138,7 @@ Examples
## update the imgData()
imgData(img_update_all(spe, brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:17.633699 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:11.011904 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 24 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/index.html b/reference/index.html
index 3d629a4c..fdcce2ae 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -249,6 +249,10 @@ All functions vis_gene()
Sample spatial gene visualization
+
+
+ Sample spatial gene visualization workhorse function
diff --git a/reference/layer_boxplot-1.png b/reference/layer_boxplot-1.png
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diff --git a/reference/layer_boxplot-5.png b/reference/layer_boxplot-5.png
index 14ac9b54..c8eb3bae 100644
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diff --git a/reference/layer_boxplot-6.png b/reference/layer_boxplot-6.png
index f44309f3..5dea49a5 100644
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diff --git a/reference/layer_boxplot-7.png b/reference/layer_boxplot-7.png
index f6564386..a247b555 100644
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diff --git a/reference/layer_boxplot.html b/reference/layer_boxplot.html
index 90de61cd..302acf11 100644
--- a/reference/layer_boxplot.html
+++ b/reference/layer_boxplot.html
@@ -65,7 +65,7 @@
Layer-level (group-level) boxplots
- Source: R/layer_boxplot.R
+ Source: R/layer_boxplot.R
layer_boxplot.Rd
@@ -185,11 +185,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:28.442408 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:28.503014 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:29.096088 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:29.384093 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Top 2 genes from the enrichment model
sig_genes <- sig_genes_extract_all(
diff --git a/reference/layer_matrix_plot-1.png b/reference/layer_matrix_plot-1.png
index d9460395..4f269d7a 100644
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diff --git a/reference/layer_matrix_plot-2.png b/reference/layer_matrix_plot-2.png
index 8e3e7d6d..2f29029a 100644
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diff --git a/reference/layer_matrix_plot.html b/reference/layer_matrix_plot.html
index d2728bb4..d5cd6750 100644
--- a/reference/layer_matrix_plot.html
+++ b/reference/layer_matrix_plot.html
@@ -66,7 +66,7 @@
Visualize a matrix of values across human brain layers
- Source: R/layer_matrix_plot.R
+ Source: R/layer_matrix_plot.R
layer_matrix_plot.Rd
diff --git a/reference/layer_stat_cor.html b/reference/layer_stat_cor.html
index be43eee0..208b193a 100644
--- a/reference/layer_stat_cor.html
+++ b/reference/layer_stat_cor.html
@@ -63,7 +63,7 @@
Layer modeling correlation of statistics
- Source: R/layer_stat_cor.R
+ Source: R/layer_stat_cor.R
layer_stat_cor.Rd
@@ -156,8 +156,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:31.53213 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:32.756558 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/layer_stat_cor_plot-1.png b/reference/layer_stat_cor_plot-1.png
index 5019ec42..72baf49d 100644
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index bdb90ead..d7368ed7 100644
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diff --git a/reference/layer_stat_cor_plot-3.png b/reference/layer_stat_cor_plot-3.png
index c9a9bcf0..4b97784a 100644
Binary files a/reference/layer_stat_cor_plot-3.png and b/reference/layer_stat_cor_plot-3.png differ
diff --git a/reference/layer_stat_cor_plot-4.png b/reference/layer_stat_cor_plot-4.png
index ee32ca9a..d74ca04c 100644
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diff --git a/reference/layer_stat_cor_plot-5.png b/reference/layer_stat_cor_plot-5.png
index 2e2b880f..a6ca399d 100644
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diff --git a/reference/layer_stat_cor_plot.html b/reference/layer_stat_cor_plot.html
index d08a54a2..7670f03a 100644
--- a/reference/layer_stat_cor_plot.html
+++ b/reference/layer_stat_cor_plot.html
@@ -66,7 +66,7 @@
Visualize the layer modeling correlation of statistics
- Source: R/layer_stat_cor_plot.R
+ Source: R/layer_stat_cor_plot.R
layer_stat_cor_plot.Rd
@@ -145,8 +145,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:32.436771 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:33.883339 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/libd_layer_colors.html b/reference/libd_layer_colors.html
index d2df282e..6a843fec 100644
--- a/reference/libd_layer_colors.html
+++ b/reference/libd_layer_colors.html
@@ -64,7 +64,7 @@
diff --git a/reference/locate_images.html b/reference/locate_images.html
index 62727198..8cbe293c 100644
--- a/reference/locate_images.html
+++ b/reference/locate_images.html
@@ -65,7 +65,7 @@
diff --git a/reference/multi_gene_pca.html b/reference/multi_gene_pca.html
index 58575a98..334fbe7d 100644
--- a/reference/multi_gene_pca.html
+++ b/reference/multi_gene_pca.html
@@ -68,7 +68,7 @@
Combine multiple continuous variables through PCA
- Source: R/multi_gene_pca.R
+ Source: R/multi_gene_pca.R
multi_gene_pca.Rd
diff --git a/reference/multi_gene_sparsity.html b/reference/multi_gene_sparsity.html
index 042ec2af..2ababa43 100644
--- a/reference/multi_gene_sparsity.html
+++ b/reference/multi_gene_sparsity.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by proportion of positive values
- Source: R/multi_gene_sparsity.R
+ Source: R/multi_gene_sparsity.R
multi_gene_sparsity.Rd
diff --git a/reference/multi_gene_z_score.html b/reference/multi_gene_z_score.html
index 612273f5..ce8a878a 100644
--- a/reference/multi_gene_z_score.html
+++ b/reference/multi_gene_z_score.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by averaging Z scores
- Source: R/multi_gene_z_score.R
+ Source: R/multi_gene_z_score.R
multi_gene_z_score.Rd
diff --git a/reference/prep_stitched_data.html b/reference/prep_stitched_data.html
index 0c4a592e..36678e3a 100644
--- a/reference/prep_stitched_data.html
+++ b/reference/prep_stitched_data.html
@@ -68,7 +68,7 @@
Prepare stitched data for plotting
- Source: R/prep_stitched_data.R
+ Source: R/prep_stitched_data.R
prep_stitched_data.Rd
diff --git a/reference/read10xVisiumAnalysis.html b/reference/read10xVisiumAnalysis.html
index b36ef451..7e04bd5b 100644
--- a/reference/read10xVisiumAnalysis.html
+++ b/reference/read10xVisiumAnalysis.html
@@ -64,7 +64,7 @@
Load analysis data from a 10x Genomics Visium experiment
- Source: R/read10xVisiumAnalysis.R
+ Source: R/read10xVisiumAnalysis.R
read10xVisiumAnalysis.Rd
@@ -118,7 +118,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/read10xVisiumWrapper.html b/reference/read10xVisiumWrapper.html
index 56b267a0..c8d01991 100644
--- a/reference/read10xVisiumWrapper.html
+++ b/reference/read10xVisiumWrapper.html
@@ -66,7 +66,7 @@
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
- Source: R/read10xVisiumWrapper.R
+ Source: R/read10xVisiumWrapper.R
read10xVisiumWrapper.Rd
@@ -162,7 +162,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/registration_block_cor.html b/reference/registration_block_cor.html
index 33000024..126fabd2 100644
--- a/reference/registration_block_cor.html
+++ b/reference/registration_block_cor.html
@@ -66,7 +66,7 @@
Spatial registration: block correlation
- Source: R/registration_block_cor.R
+ Source: R/registration_block_cor.R
registration_block_cor.Rd
@@ -121,36 +121,36 @@ See also
Examples
example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:34.847415 make pseudobulk object
-#> 2024-07-16 17:02:34.953364 drop lowly expressed genes
-#> 2024-07-16 17:02:34.99097 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:37.088175 make pseudobulk object
+#> 2024-07-17 13:51:37.267087 drop lowly expressed genes
+#> 2024-07-17 13:51:37.336566 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -179,10 +179,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:35.032307 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:37.415555 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -198,8 +198,8 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:35.038484 run duplicateCorrelation()
-#> 2024-07-16 17:02:35.564971 The estimated correlation is: -0.0187869166526901
+#> 2024-07-17 13:51:37.428263 run duplicateCorrelation()
+#> 2024-07-17 13:51:38.691552 The estimated correlation is: -0.0187869166526901
diff --git a/reference/registration_model.html b/reference/registration_model.html
index 7a26252f..c96dc0da 100644
--- a/reference/registration_model.html
+++ b/reference/registration_model.html
@@ -67,7 +67,7 @@
Spatial registration: model
- Source: R/registration_model.R
+ Source: R/registration_model.R
registration_model.Rd
@@ -125,34 +125,34 @@ See also
Examples
example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:35.873124 make pseudobulk object
-#> 2024-07-16 17:02:35.960837 drop lowly expressed genes
-#> 2024-07-16 17:02:35.986325 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:39.129951 make pseudobulk object
+#> 2024-07-17 13:51:39.31554 drop lowly expressed genes
+#> 2024-07-17 13:51:39.370617 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -181,7 +181,7 @@ Examples
#> D_S S D 14
#> E_S S E 11
registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:36.024617 create model matrix
+#> 2024-07-17 13:51:39.447064 create model matrix
head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
diff --git a/reference/registration_pseudobulk.html b/reference/registration_pseudobulk.html
index 653d03b2..8722ef39 100644
--- a/reference/registration_pseudobulk.html
+++ b/reference/registration_pseudobulk.html
@@ -64,7 +64,7 @@
Spatial registration: pseudobulk
- Source: R/registration_pseudobulk.R
+ Source: R/registration_pseudobulk.R
registration_pseudobulk.Rd
@@ -159,9 +159,9 @@ Examples
## Pseudo-bulk
sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.341187 make pseudobulk object
-#> 2024-07-16 17:02:36.4321 drop lowly expressed genes
-#> 2024-07-16 17:02:36.458483 normalize expression
+#> 2024-07-17 13:51:39.903902 make pseudobulk object
+#> 2024-07-17 13:51:40.056716 drop lowly expressed genes
+#> 2024-07-17 13:51:40.111023 normalize expression
colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
diff --git a/reference/registration_stats_anova.html b/reference/registration_stats_anova.html
index 1cf15645..cdc9d765 100644
--- a/reference/registration_stats_anova.html
+++ b/reference/registration_stats_anova.html
@@ -66,7 +66,7 @@
Spatial registration: compute ANOVA statistics
- Source: R/registration_stats_anova.R
+ Source: R/registration_stats_anova.R
registration_stats_anova.Rd
@@ -153,38 +153,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.908 make pseudobulk object
-#> 2024-07-16 17:02:36.981269 drop lowly expressed genes
-#> 2024-07-16 17:02:37.007143 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:40.701746 make pseudobulk object
+#> 2024-07-17 13:51:40.884268 drop lowly expressed genes
+#> 2024-07-17 13:51:40.939518 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -213,10 +213,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:37.061168 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:41.012467 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -232,14 +232,14 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:37.066375 run duplicateCorrelation()
-#> 2024-07-16 17:02:37.583667 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:41.024125 run duplicateCorrelation()
+#> 2024-07-17 13:51:42.289985 The estimated correlation is: -0.0187869166526901
results_anova <- registration_stats_anova(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.589856 computing F-statistics
+#> 2024-07-17 13:51:42.302664 computing F-statistics
head(results_anova)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1328075 0.93918553 0.9951876 5.499488 ENSG1 gene1
@@ -254,7 +254,7 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.615244 computing F-statistics
+#> 2024-07-17 13:51:42.365534 computing F-statistics
head(results_anova_nan)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1357180 0.93736053 0.9943765 5.499488 ENSG1 gene1
@@ -276,7 +276,7 @@ Examples
covars = NULL,
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "nocovar"
)
-#> 2024-07-16 17:02:37.632809 computing F-statistics
+#> 2024-07-17 13:51:42.415614 computing F-statistics
head(results_anova_nocovar)
#> f_stat_nocovar p_value_nocovar fdr_nocovar AveExpr_nocovar ensembl gene
#> 1 0.1393641 0.9351345 0.9962097 5.499488 ENSG1 gene1
diff --git a/reference/registration_stats_enrichment.html b/reference/registration_stats_enrichment.html
index c2fc717e..b97c7f9c 100644
--- a/reference/registration_stats_enrichment.html
+++ b/reference/registration_stats_enrichment.html
@@ -65,7 +65,7 @@
Spatial registration: compute enrichment statistics
- Source: R/registration_stats_enrichment.R
+ Source: R/registration_stats_enrichment.R
registration_stats_enrichment.Rd
@@ -144,38 +144,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:37.992936 make pseudobulk object
-#> 2024-07-16 17:02:38.06571 drop lowly expressed genes
-#> 2024-07-16 17:02:38.091375 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:42.992514 make pseudobulk object
+#> 2024-07-17 13:51:43.146693 drop lowly expressed genes
+#> 2024-07-17 13:51:43.201202 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -204,10 +204,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:38.129501 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:43.274381 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -223,15 +223,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:38.134799 run duplicateCorrelation()
-#> 2024-07-16 17:02:38.654908 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:43.285637 run duplicateCorrelation()
+#> 2024-07-17 13:51:44.583617 The estimated correlation is: -0.0187869166526901
results_enrichment <- registration_stats_enrichment(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.657236 computing enrichment statistics
-#> 2024-07-16 17:02:38.701689 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.587859 computing enrichment statistics
+#> 2024-07-17 13:51:44.705956 extract and reformat enrichment results
head(results_enrichment)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1482017 0.5610669 -0.3612235 -0.3458508 0.88374480 0.58130631
@@ -260,8 +260,8 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.712787 computing enrichment statistics
-#> 2024-07-16 17:02:38.771541 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.739083 computing enrichment statistics
+#> 2024-07-17 13:51:44.842281 extract and reformat enrichment results
head(results_enrichment_nan)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1497747 0.56711100 -0.3650801 -0.3495404 0.88252049 0.57727506
diff --git a/reference/registration_stats_pairwise.html b/reference/registration_stats_pairwise.html
index c11a5e44..03bff131 100644
--- a/reference/registration_stats_pairwise.html
+++ b/reference/registration_stats_pairwise.html
@@ -66,7 +66,7 @@
Spatial registration: compute pairwise statistics
- Source: R/registration_stats_pairwise.R
+ Source: R/registration_stats_pairwise.R
registration_stats_pairwise.Rd
@@ -146,38 +146,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:39.085978 make pseudobulk object
-#> 2024-07-16 17:02:39.159736 drop lowly expressed genes
-#> 2024-07-16 17:02:39.185678 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:45.303165 make pseudobulk object
+#> 2024-07-17 13:51:45.456984 drop lowly expressed genes
+#> 2024-07-17 13:51:45.511196 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -206,10 +206,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:39.224065 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:45.621594 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -225,15 +225,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:39.22931 run duplicateCorrelation()
-#> 2024-07-16 17:02:39.781072 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:45.632849 run duplicateCorrelation()
+#> 2024-07-17 13:51:46.88774 The estimated correlation is: -0.0187869166526901
results_pairwise <- registration_stats_pairwise(sce_pseudo,
registration_mod, block_cor,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.782515 running the baseline pairwise model
-#> 2024-07-16 17:02:39.790292 computing pairwise statistics
+#> 2024-07-17 13:51:46.889688 running the baseline pairwise model
+#> 2024-07-17 13:51:46.906431 computing pairwise statistics
head(results_pairwise)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2393683 0.29771391 0.28880637 0.5370822 0.5281747
@@ -277,8 +277,8 @@ Examples
block_cor = NaN,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.811874 running the baseline pairwise model
-#> 2024-07-16 17:02:39.818697 computing pairwise statistics
+#> 2024-07-17 13:51:46.971696 running the baseline pairwise model
+#> 2024-07-17 13:51:46.989106 computing pairwise statistics
head(results_pairwise_nan)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2419770 0.30095840 0.29195379 0.5429354 0.5339308
diff --git a/reference/registration_wrapper.html b/reference/registration_wrapper.html
index 546b32eb..a04252d2 100644
--- a/reference/registration_wrapper.html
+++ b/reference/registration_wrapper.html
@@ -68,7 +68,7 @@
Spatial registration: wrapper function
- Source: R/registration_wrapper.R
+ Source: R/registration_wrapper.R
registration_wrapper.Rd
@@ -200,18 +200,18 @@ Examples
sce,
"Cell_Cycle", "sample_id", c("age"), "ensembl", "gene_name", "wrapper"
)
-#> 2024-07-16 17:02:40.149028 make pseudobulk object
-#> 2024-07-16 17:02:40.221379 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:02:40.231996 drop lowly expressed genes
-#> 2024-07-16 17:02:40.27465 normalize expression
-#> 2024-07-16 17:02:40.303232 create model matrix
-#> 2024-07-16 17:02:40.308019 run duplicateCorrelation()
-#> 2024-07-16 17:02:41.300298 The estimated correlation is: -0.0783081238514527
-#> 2024-07-16 17:02:41.301437 computing enrichment statistics
-#> 2024-07-16 17:02:41.342436 extract and reformat enrichment results
-#> 2024-07-16 17:02:41.35071 running the baseline pairwise model
-#> 2024-07-16 17:02:41.357315 computing pairwise statistics
-#> 2024-07-16 17:02:41.380689 computing F-statistics
+#> 2024-07-17 13:51:47.541862 make pseudobulk object
+#> 2024-07-17 13:51:47.707925 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:51:47.729853 drop lowly expressed genes
+#> 2024-07-17 13:51:47.785167 normalize expression
+#> 2024-07-17 13:51:47.8429 create model matrix
+#> 2024-07-17 13:51:47.853499 run duplicateCorrelation()
+#> 2024-07-17 13:51:50.267571 The estimated correlation is: -0.0783081238514532
+#> 2024-07-17 13:51:50.269845 computing enrichment statistics
+#> 2024-07-17 13:51:50.386595 extract and reformat enrichment results
+#> 2024-07-17 13:51:50.412505 running the baseline pairwise model
+#> 2024-07-17 13:51:50.430847 computing pairwise statistics
+#> 2024-07-17 13:51:50.505218 computing F-statistics
diff --git a/reference/run_app.html b/reference/run_app.html
index d23cb924..2cca4ddc 100644
--- a/reference/run_app.html
+++ b/reference/run_app.html
@@ -65,7 +65,7 @@
@@ -270,7 +270,7 @@ Examples
vars <- colnames(colData(spe))
## Set default cluster colors
- colors_BayesSpace <- Polychrome::palette36.colors(28)
+ colors_BayesSpace <- Polychrome::palette36.colors(28)
names(colors_BayesSpace) <- c(1:28)
m <- match(as.character(spe$BayesSpace_harmony_09), names(colors_BayesSpace))
stopifnot(all(!is.na(m)))
diff --git a/reference/sce_to_spe.html b/reference/sce_to_spe.html
index 84fd3093..e0797fb6 100644
--- a/reference/sce_to_spe.html
+++ b/reference/sce_to_spe.html
@@ -67,7 +67,7 @@
@@ -127,8 +127,7 @@ Examples
## Transform it to a SpatialExperiment object
spe <- sce_to_spe(sce)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:43.103369 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:52.727073 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/sig_genes_extract.html b/reference/sig_genes_extract.html
index 0ecdbcc3..4c448c85 100644
--- a/reference/sig_genes_extract.html
+++ b/reference/sig_genes_extract.html
@@ -67,7 +67,7 @@
Extract significant genes
- Source: R/sig_genes_extract.R
+ Source: R/sig_genes_extract.R
sig_genes_extract.Rd
@@ -156,11 +156,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:52.484674 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:05.714888 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:53.182388 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:06.659035 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## anova top 10 genes
sig_genes_extract(
diff --git a/reference/sig_genes_extract_all.html b/reference/sig_genes_extract_all.html
index 17516a57..4a42f61e 100644
--- a/reference/sig_genes_extract_all.html
+++ b/reference/sig_genes_extract_all.html
@@ -65,7 +65,7 @@
Extract significant genes for all modeling results
- Source: R/sig_genes_extract_all.R
+ Source: R/sig_genes_extract_all.R
sig_genes_extract_all.Rd
@@ -128,11 +128,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.422915 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:10.311903 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.970561 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:11.371345 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## top 10 genes for all models
sig_genes_extract_all(
diff --git a/reference/sort_clusters.html b/reference/sort_clusters.html
index 8dccd3d7..675c4397 100644
--- a/reference/sort_clusters.html
+++ b/reference/sort_clusters.html
@@ -65,7 +65,7 @@
diff --git a/reference/spatialLIBD-package.html b/reference/spatialLIBD-package.html
index 148e52f3..c22a18c2 100644
--- a/reference/spatialLIBD-package.html
+++ b/reference/spatialLIBD-package.html
@@ -64,7 +64,7 @@
spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
- Source: R/spatialLIBD-package.R
+ Source: R/spatialLIBD-package.R
spatialLIBD-package.Rd
diff --git a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
index e6a4ba86..4dbbeb2a 100644
--- a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
+++ b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
@@ -69,7 +69,7 @@
Cell cluster t-statistics from Tran et al
- Source: R/data.R
+ Source: R/data.R
tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.Rd
diff --git a/reference/vis_clus-1.png b/reference/vis_clus-1.png
index b62ae3bc..fff9298e 100644
Binary files a/reference/vis_clus-1.png and b/reference/vis_clus-1.png differ
diff --git a/reference/vis_clus-2.png b/reference/vis_clus-2.png
index 59f18aa4..4962aaef 100644
Binary files a/reference/vis_clus-2.png and b/reference/vis_clus-2.png differ
diff --git a/reference/vis_clus-3.png b/reference/vis_clus-3.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus-4.png b/reference/vis_clus-4.png
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diff --git a/reference/vis_clus.html b/reference/vis_clus.html
index 4c441931..29b47fed 100644
--- a/reference/vis_clus.html
+++ b/reference/vis_clus.html
@@ -65,7 +65,7 @@
@@ -242,8 +242,7 @@ Examples
)
print(p4)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:57.892758 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:14.053539 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_clus_p-1.png b/reference/vis_clus_p-1.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus_p.html b/reference/vis_clus_p.html
index 0106b4be..1e416396 100644
--- a/reference/vis_clus_p.html
+++ b/reference/vis_clus_p.html
@@ -66,7 +66,7 @@
Sample spatial cluster visualization workhorse function
- Source: R/vis_clus_p.R
+ Source: R/vis_clus_p.R
vis_clus_p.Rd
@@ -74,7 +74,7 @@ Sample spatial cluster visualization workhorse function
This function visualizes the clusters for one given sample at the spot-level
using (by default) the histology information on the background. This is the
function that does all the plotting behind vis_clus(). To visualize
-gene-level (or any continuous variable) use vis_gene_p().
+gene-level (or any continuous variable) use vis_gene_p().
@@ -202,8 +202,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:12.064384 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:33.265544 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene-1.png b/reference/vis_gene-1.png
index dd3f3f08..3585ea9b 100644
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diff --git a/reference/vis_gene-10.png b/reference/vis_gene-10.png
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diff --git a/reference/vis_gene-2.png b/reference/vis_gene-2.png
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diff --git a/reference/vis_gene-5.png b/reference/vis_gene-5.png
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diff --git a/reference/vis_gene-6.png b/reference/vis_gene-6.png
index 528c1c2a..9eccafab 100644
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diff --git a/reference/vis_gene-7.png b/reference/vis_gene-7.png
index da60a0bf..c26013a0 100644
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diff --git a/reference/vis_gene-8.png b/reference/vis_gene-8.png
index 2e73ba4d..a91893cf 100644
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diff --git a/reference/vis_gene-9.png b/reference/vis_gene-9.png
index 9123b986..fa2c6a94 100644
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diff --git a/reference/vis_gene.html b/reference/vis_gene.html
index e39667fc..f0e49f68 100644
--- a/reference/vis_gene.html
+++ b/reference/vis_gene.html
@@ -66,7 +66,7 @@
@@ -220,12 +220,12 @@ Value
Details
This function subsets spe to the given sample and prepares the
-data and title for vis_gene_p(). It also adds a caption to the plot.
+data and title for vis_gene_p(). It also adds a caption to the plot.
See also
Other Spatial gene visualization functions:
-vis_gene_p(),
+vis_gene_p(),
vis_grid_gene()
@@ -341,8 +341,7 @@ Examples
)
print(p8)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:22.728238 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:48.10019 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene_p-1.png b/reference/vis_gene_p-1.png
new file mode 100644
index 00000000..24287b46
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diff --git a/reference/vis_gene_p.html b/reference/vis_gene_p.html
new file mode 100644
index 00000000..4f32d6a8
--- /dev/null
+++ b/reference/vis_gene_p.html
@@ -0,0 +1,245 @@
+
+Sample spatial gene visualization workhorse function — vis_gene_p • spatialLIBD
+
+
+
+
+
+
+
+
+
+
+
+
+ This function visualizes the gene expression stored in assays(spe) or any
+continuous variable stored in colData(spe) for one given sample at the
+spot-level using (by default) the histology information on the background.
+This is the function that does all the plotting behind vis_gene()
+To visualize clusters (or any discrete variable) use vis_clus_p().
+
+
+
+ vis_gene_p(
+ spe,
+ d,
+ sampleid = unique(spe$sample_id)[1],
+ spatial,
+ title,
+ viridis = TRUE,
+ image_id = "lowres",
+ alpha = NA,
+ cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4",
+ "springgreen", "goldenrod", "red"),
+ point_size = 2,
+ auto_crop = TRUE,
+ na_color = "#CCCCCC40",
+ legend_title = ""
+)
+
+
+
+ Arguments
+
+
+- spe
+A
+SpatialExperiment-class
+object. See fetch_data() for how to download some example objects or
+read10xVisiumWrapper() to read in spaceranger --count output files and
+build your own spe object.
- d
+A data.frame() with the sample-level information. This is
+typically obtained using cbind(colData(spe), spatialCoords(spe)).
+The data.frame has to contain
+a column with the continuous variable data to plot stored under d$COUNT.
- sampleid
+A character(1) specifying which sample to plot from
+colData(spe)$sample_id (formerly colData(spe)$sample_name).
- spatial
+A logical(1) indicating whether to include the histology
+layer from geom_spatial(). If you plan to use
+ggplotly() then it's best to set this to FALSE.
- title
+The title for the plot.
- viridis
+A logical(1) whether to use the color-blind friendly
+palette from viridis or the color palette used
+in the paper that was chosen for contrast when visualizing the data on
+top of the histology image. One issue is being able to differentiate low
+values from NA ones due to the purple-ish histology information that is
+dependent on cell density.
- image_id
+A character(1) with the name of the image ID you want to
+use in the background.
- alpha
+A numeric(1) in the [0, 1] range that specifies the
+transparency level of the data on the spots.
- cont_colors
+A character() vector of colors that supersedes the
+viridis argument.
- point_size
+A numeric(1) specifying the size of the points. Defaults
+to 1.25. Some colors look better if you use 2 for instance.
- auto_crop
+A logical(1) indicating whether to automatically crop
+the image / plotting area, which is useful if the Visium capture area is
+not centered on the image and if the image is not a square.
- na_color
+A character(1) specifying a color for the NA values.
+If you set alpha = NA then it's best to set na_color to a color that has
+alpha blending already, which will make non-NA values pop up more and the NA
+values will show with a lighter color. This behavior is lost when alpha is
+set to a non-NA value.
- legend_title
+A character(1) specifying the legend title.
+
+ Value
+ A ggplot2 object.
+
+
+ See also
+ Other Spatial gene visualization functions:
+vis_gene(),
+vis_grid_gene()
+
+
+
+ Examples
+
+if (enough_ram()) {
+ ## Obtain the necessary data
+ if (!exists("spe")) spe <- fetch_data("spe")
+
+ ## Prepare the data for the plotting function
+ spe_sub <- spe[, spe$sample_id == "151673"]
+ df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
+ df$COUNT <- df$expr_chrM_ratio
+
+ ## Don't plot the histology information
+ p <- vis_gene_p(
+ spe = spe_sub,
+ d = df,
+ sampleid = "151673",
+ title = "151673 chrM expr ratio",
+ spatial = FALSE
+ )
+ print(p)
+
+ ## Clean up
+ rm(spe_sub)
+}
+#> 2024-07-17 13:53:14.003193 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/reference/vis_grid_clus-1.png b/reference/vis_grid_clus-1.png
index fc3c2d6c..ea564e20 100644
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diff --git a/reference/vis_grid_clus.html b/reference/vis_grid_clus.html
index beb4cdd7..a1aec073 100644
--- a/reference/vis_grid_clus.html
+++ b/reference/vis_grid_clus.html
@@ -65,7 +65,7 @@
Sample spatial cluster visualization grid
- Source: R/vis_grid_clus.R
+ Source: R/vis_grid_clus.R
vis_grid_clus.Rd
@@ -237,8 +237,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:41.57373 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:29.053452 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_grid_gene-1.png b/reference/vis_grid_gene-1.png
index d8f795d8..b246fec3 100644
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diff --git a/reference/vis_grid_gene.html b/reference/vis_grid_gene.html
index f5428110..7f5c56b0 100644
--- a/reference/vis_grid_gene.html
+++ b/reference/vis_grid_gene.html
@@ -66,7 +66,7 @@
Sample spatial gene visualization grid
- Source: R/vis_grid_gene.R
+ Source: R/vis_grid_gene.R
vis_grid_gene.Rd
@@ -234,7 +234,7 @@ Details
See also
Other Spatial gene visualization functions:
vis_gene(),
-vis_gene_p()
+vis_gene_p()
@@ -256,8 +256,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:53.38865 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:45.486537 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/sitemap.xml b/sitemap.xml
index d4f77066..8a33c15f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -62,6 +62,7 @@
/reference/vis_clus.html /reference/vis_clus_p.html /reference/vis_gene.html /reference/vis_gene_p.html /reference/vis_grid_clus.html /reference/vis_grid_gene.html
Wrapper functions= c("lowres", "hires", "detected", "aligned"), load = TRUE,
reference_gtf = gtf_cache
)
-#> 2024-07-16 17:06:02.30044 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
-#> 2024-07-16 17:06:10.20779 read10xVisiumAnalysis: reading analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.42459 add10xVisiumAnalysis: adding analysis output from SpaceRanger
-#> 2024-07-16 17:06:11.61105 rtracklayer::import: reading the reference GTF file
-#> 2024-07-16 17:06:31.708652 adding gene information to the SPE object
+#> 2024-07-17 13:57:08.168846 SpatialExperiment::read10xVisium: reading basic data from SpaceRanger
+#> 2024-07-17 13:57:19.596362 read10xVisiumAnalysis: reading analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.702059 add10xVisiumAnalysis: adding analysis output from SpaceRanger
+#> 2024-07-17 13:57:19.945565 rtracklayer::import: reading the reference GTF file
+#> 2024-07-17 13:57:47.519521 adding gene information to the SPE object
#> Warning: Gene IDs did not match. This typically happens when you are not using
#> the same GTF file as the one that was used by SpaceRanger. For example, one
#> file uses GENCODE IDs and the other one ENSEMBL IDs. read10xVisiumWrapper()
@@ -832,7 +830,7 @@ Wrapper functions#> Warning: Dropping 29 out of 36601 genes for which we don't have information on
#> the reference GTF file. This typically happens when you are not using the same
#> GTF file as the one that was used by SpaceRanger.
-#> 2024-07-16 17:06:31.907411 adding information used by spatialLIBD
+#> 2024-07-17 13:57:47.776325 adding information used by spatialLIBD
## Run our shiny app
if (interactive()) {
@@ -1116,200 +1114,202 @@ Reproducibilitylibrary("knitr")
knit("TenX_data_download.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:06:32 EDT"
+#> [1] "2024-07-17 13:57:48 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 1.183 mins
+#> Time difference of 1.705 mins
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
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+#> stringr 1.5.1 2023-11-14 [2] RSPM (R 4.4.0)
+#> SummarizedExperiment * 1.34.0 2024-05-01 [1] Bioconductor 3.19 (R 4.4.1)
+#> systemfonts 1.1.0 2024-05-15 [2] RSPM (R 4.4.0)
+#> textshaping 0.4.0 2024-05-24 [2] RSPM (R 4.4.0)
+#> tibble 3.2.1 2023-03-20 [2] RSPM (R 4.4.0)
+#> tidyr 1.3.1 2024-01-24 [1] RSPM (R 4.4.0)
+#> tidyselect 1.2.1 2024-03-11 [1] RSPM (R 4.4.0)
+#> timechange 0.3.0 2024-01-18 [1] RSPM (R 4.4.0)
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+#> viridis 0.6.5 2024-01-29 [1] RSPM (R 4.4.0)
+#> viridisLite 0.4.2 2023-05-02 [1] RSPM (R 4.4.0)
+#> withr 3.0.0 2024-01-16 [2] RSPM (R 4.4.0)
+#> xfun 0.45 2024-06-16 [2] RSPM (R 4.4.0)
+#> XML 3.99-0.17 2024-06-25 [1] RSPM (R 4.4.0)
+#> xml2 1.3.6 2023-12-04 [2] RSPM (R 4.4.0)
+#> xtable 1.8-4 2019-04-21 [2] RSPM (R 4.4.0)
+#> XVector 0.44.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
+#> yaml 2.3.9 2024-07-05 [2] RSPM (R 4.4.0)
+#> zlibbioc 1.50.0 2024-04-30 [1] Bioconductor 3.19 (R 4.4.1)
#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -1356,8 +1356,10 @@ Bibliography[5]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[6]
@@ -1385,13 +1387,16 @@ Bibliography[9]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[10]
H. Wickham. lobstr: Visualize R Data Structures with Trees. R
-package version 1.1.2. 2022. URL:
-https://CRAN.R-project.org/package=lobstr.
+package version 1.1.2, https://github.com/r-lib/lobstr. 2022. URL:
+https://lobstr.r-lib.org/.
[11]
@@ -1402,8 +1407,8 @@ Bibliography[12]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[13]
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png
index befc0397..681004b2 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png differ
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png
index 017fcd18..ac8b5fff 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png differ
diff --git a/articles/guide_to_spatial_registration.html b/articles/guide_to_spatial_registration.html
index a056ae9f..cb254465 100644
--- a/articles/guide_to_spatial_registration.html
+++ b/articles/guide_to_spatial_registration.html
@@ -101,9 +101,9 @@ Louise
Development
lahuuki@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/guide_to_spatial_registration.Rmd
+ Source: vignettes/guide_to_spatial_registration.Rmd
guide_to_spatial_registration.Rmd
@@ -268,8 +268,6 @@ Load required packages
library("spatialLIBD")
-#> Warning: package 'S4Vectors' was built under R version 4.4.1
-#> Warning: package 'IRanges' was built under R version 4.4.1
library("SingleCellExperiment")
@@ -290,7 +288,7 @@ Spatial Reference
## get reference layer enrichment statistics
layer_modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:13.829724 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:54:13.294755 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
layer_modeling_results$enrichment[1:5, 1:5]
#> t_stat_WM t_stat_Layer1 t_stat_Layer2 t_stat_Layer3 t_stat_Layer4
@@ -393,18 +391,18 @@ Get Enrichment statistics
gene_ensembl = "gene_id",
gene_name = "gene_name"
)
-#> 2024-07-16 17:04:17.342908 make pseudobulk object
-#> 2024-07-16 17:04:18.696265 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:04:18.724833 drop lowly expressed genes
-#> 2024-07-16 17:04:18.799779 normalize expression
-#> 2024-07-16 17:04:19.584255 create model matrix
-#> 2024-07-16 17:04:19.595618 run duplicateCorrelation()
-#> 2024-07-16 17:04:25.229344 The estimated correlation is: 0.138734774807097
-#> 2024-07-16 17:04:25.231011 computing enrichment statistics
-#> 2024-07-16 17:04:25.960375 extract and reformat enrichment results
-#> 2024-07-16 17:04:26.003855 running the baseline pairwise model
-#> 2024-07-16 17:04:26.12952 computing pairwise statistics
-#> 2024-07-16 17:04:27.403954 computing F-statistics
+#> 2024-07-17 13:54:21.031386 make pseudobulk object
+#> 2024-07-17 13:54:22.727446 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:54:22.789323 drop lowly expressed genes
+#> 2024-07-17 13:54:22.963372 normalize expression
+#> 2024-07-17 13:54:24.427132 create model matrix
+#> 2024-07-17 13:54:24.451001 run duplicateCorrelation()
+#> 2024-07-17 13:54:37.623842 The estimated correlation is: 0.138734774807097
+#> 2024-07-17 13:54:37.626295 computing enrichment statistics
+#> 2024-07-17 13:54:38.79442 extract and reformat enrichment results
+#> 2024-07-17 13:54:38.851417 running the baseline pairwise model
+#> 2024-07-17 13:54:39.041435 computing pairwise statistics
+#> 2024-07-17 13:54:40.421524 computing F-statistics
Extract Enrichment t-statistics
@@ -564,187 +562,189 @@ Reproducibilitylibrary("knitr")
knit("guide_to_spatial_registration.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:28 EDT"
+#> [1] "2024-07-17 13:54:41 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.924 secs
+#> Time difference of 40.965 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -782,8 +782,10 @@ Bibliography[4]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[5]
@@ -817,8 +819,8 @@ Bibliography[9]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[10]
diff --git a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png
index 37955c4b..d3a2dbfd 100644
Binary files a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png and b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png differ
diff --git a/articles/multi_gene_plots.html b/articles/multi_gene_plots.html
index 684a2bbb..847ca6a7 100644
--- a/articles/multi_gene_plots.html
+++ b/articles/multi_gene_plots.html
@@ -108,9 +108,9 @@ Leonardo
Public Health
lcolladotor@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/multi_gene_plots.Rmd
+ Source: vignettes/multi_gene_plots.Rmd
multi_gene_plots.Rmd
@@ -195,9 +195,9 @@ Plotting One Gene
modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:43.021669 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:06.762958 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
sce_layer <- fetch_data(type = "sce_layer")
-#> 2024-07-16 17:04:43.645201 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:07.675711 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
sig_genes <- sig_genes_extract_all(
n = 400,
modeling_results = modeling_results,
@@ -421,189 +421,191 @@ Reproducibilitylibrary("knitr")
knit("multi_gene_plots.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:04:53 EDT"
+#> [1] "2024-07-17 13:55:23 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 21.564 secs
+#> Time difference of 36.887 secs
R session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
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diff --git a/articles/spatialLIBD.html b/articles/spatialLIBD.html
index 241db4f0..3e707196 100644
--- a/articles/spatialLIBD.html
+++ b/articles/spatialLIBD.html
@@ -114,9 +114,9 @@ Andrew E.
Campus
andrew.jaffe@libd.org
- 16 July 2024
+ 17 July 2024
- Source: vignettes/spatialLIBD.Rmd
+ Source: vignettes/spatialLIBD.Rmd
spatialLIBD.Rmd
@@ -414,7 +414,7 @@ Downloading the data with s
## Download the small example sce data
sce <- fetch_data(type = "sce_example", eh = ehub)
-#> 2024-07-16 17:05:03.908351 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:39.830372 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
## Convert to a SpatialExperiment object
spe <- sce_to_spe(sce)
@@ -426,9 +426,9 @@ Downloading the data with s
## Query ExperimentHub and download the data
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer", eh = ehub)
-#> 2024-07-16 17:05:07.931392 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.107964 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
modeling_results <- fetch_data("modeling_results", eh = ehub)
-#> 2024-07-16 17:05:08.248131 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.559624 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
Once you have downloaded the objects, we can explore them a little
bit
@@ -501,7 +501,7 @@ Downloading the data with s
)
)
#> user system elapsed
-#> 5.090 0.218 5.325
+#> 9.944 0.296 10.247
## Explore the result
class(sig_genes)
@@ -707,7 +707,7 @@ Spot-level genes and continuo
the histology set of purple tones that are noticeable when the
continuous variable is below or equal to the minCount (in
our palettes such points have a 'transparent' color). For
-more details, check the internal code of vis_gene_p().
+more details, check the internal code of vis_gene_p().
Extract significant genes
@@ -1018,7 +1018,7 @@ SpatialExperiment support
As of version 1.3.3, spatialLIBD
supports the SpatialExperiment class from SpatialExperiment.
-The functions vis_gene_p(), vis_gene(),
+The functions vis_gene_p(), vis_gene(),
vis_grid_clus(), vis_grid_gene(),
vis_clus(), vis_clus_p(),
geom_spatial() now work with SpatialExperiment
@@ -1108,7 +1108,7 @@
Generating our data (legacy)vis_clus_p() and
-vis_gene_p(). Having the data from all images in a single
+vis_gene_p(). Having the data from all images in a single
object allows you to use the spot-level data from all images to compute
clusters and do other similar analyses to the ones you would do with
sc/snRNA-seq data. The script creates the
@@ -1377,189 +1377,191 @@ Reproducibilitylibrary("knitr")
knit("spatialLIBD.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:05:18 EDT"
+#> [1] "2024-07-17 13:56:02 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 22.031 secs
+#> Time difference of 34.974 secs
R session information.
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#> setting value
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+#> os Ubuntu 22.04.4 LTS
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#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
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#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
@@ -1594,8 +1596,8 @@ Bibliography[4]
W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application
-Framework for R. R package version 1.8.1.1. 2024. URL:
-https://CRAN.R-project.org/package=shiny.
+Framework for R. R package version 1.8.1.1, https://github.com/rstudio/shiny. 2024. URL:
+https://shiny.posit.co/.
[5]
@@ -1616,7 +1618,7 @@ Bibliography[7]
C. Fay, V. Guyader, S. Rochette, et al. golem: A Framework for
Robust Shiny Applications. R package version 0.4.1. 2023. URL:
-https://CRAN.R-project.org/package=golem.
+https://github.com/ThinkR-open/golem.
[8]
@@ -1630,7 +1632,7 @@ Bibliography[9]
C. Gillespie. benchmarkme: Crowd Sourced System Benchmarks. R
package version 1.0.8. 2022. URL:
-https://CRAN.R-project.org/package=benchmarkme.
+https://github.com/csgillespie/benchmarkme.
[10]
@@ -1718,42 +1720,53 @@ Bibliography[20]
M. Morgan, V. Obenchain, J. Hester, et al. SummarizedExperiment:
SummarizedExperiment container. R package version 1.34.0. 2024.
+DOI:
+10.18129/B9.bioc.SummarizedExperiment.
URL:
https://bioconductor.org/packages/SummarizedExperiment.
[21]
M. Morgan and L. Shepherd. AnnotationHub: Client to access
-AnnotationHub resources. R package version 3.12.0. 2024.
+AnnotationHub resources. R package version 3.12.0. 2024. DOI:
+10.18129/B9.bioc.AnnotationHub.
+URL:
+https://bioconductor.org/packages/AnnotationHub.
[22]
M. Morgan and L. Shepherd. ExperimentHub: Client to access
-ExperimentHub resources. R package version 2.12.0. 2024.
+ExperimentHub resources. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.ExperimentHub.
+URL:
+https://bioconductor.org/packages/ExperimentHub.
[23]
E. Neuwirth. RColorBrewer: ColorBrewer Palettes. R package
-version 1.1-3. 2022. URL:
-https://CRAN.R-project.org/package=RColorBrewer.
+version 1.1-3. 2022.
[24]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
+https://bioconductor.org/packages/BiocStyle.
[25]
J. Ooms. magick: Advanced Graphics and Image-Processing in R. R
-package version 2.8.3. 2024. URL:
-https://CRAN.R-project.org/package=magick.
+package version 2.8.4. 2024. URL:
+https://docs.ropensci.org/magick/https://ropensci.r-universe.dev/magick.
[26]
H. Pagès, M. Lawrence, and P. Aboyoun. S4Vectors: Foundation of
vector-like and list-like containers in Bioconductor. R package
-version 0.42.1. 2024. URL:
+version 0.42.1. 2024. DOI:
+10.18129/B9.bioc.S4Vectors.
+URL:
https://bioconductor.org/packages/S4Vectors.
@@ -1789,7 +1802,10 @@
Bibliography[31]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[32]
@@ -1812,14 +1828,14 @@ Bibliography[35]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[36]
C. Wilke. cowplot: Streamlined Plot Theme and Plot Annotations for
‘ggplot2’. R package version 1.1.3. 2024. URL:
-https://CRAN.R-project.org/package=cowplot.
+https://wilkelab.org/cowplot/.
[37]
@@ -1832,7 +1848,7 @@ Bibliography[38]
Y. Xie, J. Cheng, and X. Tan. DT: A Wrapper of the JavaScript
Library ‘DataTables’. R package version 0.33. 2024. URL:
-https://CRAN.R-project.org/package=DT.
+https://github.com/rstudio/DT.
diff --git a/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png b/articles/spatialLIBD_files/figure-html/layer_boxplot-1.png
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diff --git a/articles/spatialLIBD_files/figure-html/vis_gene-3.png b/articles/spatialLIBD_files/figure-html/vis_gene-3.png
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diff --git a/authors.html b/authors.html
index 3d9fe61e..5953cb2d 100644
--- a/authors.html
+++ b/authors.html
@@ -107,7 +107,7 @@ Authors and Citation
diff --git a/news/index.html b/news/index.html
index 38fa2bfe..93a36916 100644
--- a/news/index.html
+++ b/news/index.html
@@ -63,7 +63,7 @@
@@ -221,7 +221,7 @@ spatialLIBD
-
run_app() now offers the option to chose any of the paletteer::paletteer_d color palettes for discrete variables.
-
-
Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
+Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
-
run_app() now looks for columns that end with ’_colors’ in their name which can be used to pre-specify colors for any companion variables. For example if you have spe$my_groups and spe$my_groups_colors then the second one can specify the colors that will be used for visualizing spe$my_groups. This makes specifying default colors more flexible than before, and the user is still free to change them if necessary.
@@ -265,7 +265,7 @@ spatialLIBD 1
spatialLIBD 1.7.6
NEW FEATURES
-
-
vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
+vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
- The shiny app now has an input controlling the point size. If you increase it to say
5, then if you zoom in the clusters (interactive) panel, you can see larger spots when zooming in.
- These features are related to https://github.com/LieberInstitute/spatialLIBD/issues/28 although the spot diameter is still not the true spot diameter. However, now you have more flexibility for visualizing the spots.
@@ -333,7 +333,7 @@ spatialLIBD
spatialLIBD 1.3.3
NEW FEATURES
-- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
+- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
- Updated citation information to reflect that https://doi.org/10.1038/s41593-020-00787-0 is now public. Also added a link on the README to https://doi.org/10.6084/m9.figshare.13623902.v1 for the manuscript high resolution images.
diff --git a/pkgdown.yml b/pkgdown.yml
index 46fd2df0..f01eec79 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,4 +6,4 @@ articles:
multi_gene_plots: multi_gene_plots.html
spatialLIBD: spatialLIBD.html
TenX_data_download: TenX_data_download.html
-last_built: 2024-07-16T21:00Z
+last_built: 2024-07-17T13:48Z
diff --git a/reference/Rplot001.png b/reference/Rplot001.png
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diff --git a/reference/add10xVisiumAnalysis.html b/reference/add10xVisiumAnalysis.html
index da55e67a..6dd8b9b8 100644
--- a/reference/add10xVisiumAnalysis.html
+++ b/reference/add10xVisiumAnalysis.html
@@ -65,7 +65,7 @@
Add analysis data from a 10x Genomics Visium experiment to a SPE object
- Source: R/add10xVisiumAnalysis.R
+ Source: R/add10xVisiumAnalysis.R
add10xVisiumAnalysis.Rd
@@ -120,7 +120,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/add_images.html b/reference/add_images.html
index 37749b90..db2faadf 100644
--- a/reference/add_images.html
+++ b/reference/add_images.html
@@ -71,7 +71,7 @@
Add non-standard images with the same dimensions as current ones
- Source: R/add_images.R
+ Source: R/add_images.R
add_images.Rd
@@ -165,30 +165,29 @@ Examples
image_paths = c("151507" = "https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151507_tissue_lowres_image.png")
))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:18.72371 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
-#> 2024-07-16 17:00:29.794628 adding image for sample 151507
-#> 2024-07-16 17:00:30.766353 adding image for sample 151508
+#> 2024-07-17 13:48:26.600477 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:41.90188 adding image for sample 151507
+#> 2024-07-17 13:48:42.538745 adding image for sample 151508
#> Warning: No image was found for sample: 151508
-#> 2024-07-16 17:00:30.766579 adding image for sample 151509
+#> 2024-07-17 13:48:42.539054 adding image for sample 151509
#> Warning: No image was found for sample: 151509
-#> 2024-07-16 17:00:30.766725 adding image for sample 151510
+#> 2024-07-17 13:48:42.539261 adding image for sample 151510
#> Warning: No image was found for sample: 151510
-#> 2024-07-16 17:00:30.766858 adding image for sample 151669
+#> 2024-07-17 13:48:42.539459 adding image for sample 151669
#> Warning: No image was found for sample: 151669
-#> 2024-07-16 17:00:30.76698 adding image for sample 151670
+#> 2024-07-17 13:48:42.539652 adding image for sample 151670
#> Warning: No image was found for sample: 151670
-#> 2024-07-16 17:00:30.767101 adding image for sample 151671
+#> 2024-07-17 13:48:42.539843 adding image for sample 151671
#> Warning: No image was found for sample: 151671
-#> 2024-07-16 17:00:30.767222 adding image for sample 151672
+#> 2024-07-17 13:48:42.540033 adding image for sample 151672
#> Warning: No image was found for sample: 151672
-#> 2024-07-16 17:00:30.76734 adding image for sample 151673
+#> 2024-07-17 13:48:42.540223 adding image for sample 151673
#> Warning: No image was found for sample: 151673
-#> 2024-07-16 17:00:30.767458 adding image for sample 151674
+#> 2024-07-17 13:48:42.540414 adding image for sample 151674
#> Warning: No image was found for sample: 151674
-#> 2024-07-16 17:00:30.767576 adding image for sample 151675
+#> 2024-07-17 13:48:42.540604 adding image for sample 151675
#> Warning: No image was found for sample: 151675
-#> 2024-07-16 17:00:30.767696 adding image for sample 151676
+#> 2024-07-17 13:48:42.540791 adding image for sample 151676
#> Warning: No image was found for sample: 151676
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
diff --git a/reference/add_key.html b/reference/add_key.html
index 7dce6d11..220b5ded 100644
--- a/reference/add_key.html
+++ b/reference/add_key.html
@@ -65,7 +65,7 @@
@@ -124,8 +124,7 @@ Examples
spe$key_original <- NULL
head(spe$key)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:33.017537 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:44.910936 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> [1] "151507_AAACAACGAATAGTTC-1" "151507_AAACAAGTATCTCCCA-1"
#> [3] "151507_AAACAATCTACTAGCA-1" "151507_AAACACCAATAACTGC-1"
#> [5] "151507_AAACAGCTTTCAGAAG-1" "151507_AAACAGGGTCTATATT-1"
diff --git a/reference/add_qc_metrics-1.png b/reference/add_qc_metrics-1.png
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diff --git a/reference/add_qc_metrics.html b/reference/add_qc_metrics.html
index db6a4d92..9c72a786 100644
--- a/reference/add_qc_metrics.html
+++ b/reference/add_qc_metrics.html
@@ -67,7 +67,7 @@
Quality Control for Spatial Data
- Source: R/add_qc_metrics.R
+ Source: R/add_qc_metrics.R
add_qc_metrics.Rd
@@ -144,8 +144,7 @@ Author
Examples
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:43.634355 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f563a40ecf7_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
+#> 2024-07-17 13:49:00.582195 loading file /github/home/.cache/R/BiocFileCache/49872dc0d45_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
diff --git a/reference/annotate_registered_clusters.html b/reference/annotate_registered_clusters.html
index fd6421d6..50b43af5 100644
--- a/reference/annotate_registered_clusters.html
+++ b/reference/annotate_registered_clusters.html
@@ -67,7 +67,7 @@
Annotated spatially-registered clusters
- Source: R/annotate_registered_clusters.R
+ Source: R/annotate_registered_clusters.R
annotate_registered_clusters.Rd
@@ -137,8 +137,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:51.762523 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:13.326528 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/check_modeling_results.html b/reference/check_modeling_results.html
index e56f7419..f95254df 100644
--- a/reference/check_modeling_results.html
+++ b/reference/check_modeling_results.html
@@ -64,7 +64,7 @@
Check input modeling_results
- Source: R/check_modeling_results.R
+ Source: R/check_modeling_results.R
check_modeling_results.Rd
@@ -108,8 +108,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:52.678188 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:14.441658 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Check the object
xx <- check_modeling_results(modeling_results)
diff --git a/reference/check_sce.html b/reference/check_sce.html
index 8a937cdf..fdc02746 100644
--- a/reference/check_sce.html
+++ b/reference/check_sce.html
@@ -66,7 +66,7 @@
@@ -131,8 +131,7 @@ Examples
## Check the object
check_sce(sce_example)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:53.63802 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:15.651297 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
#> class: SingleCellExperiment
#> dim: 33538 47681
#> metadata(1): image
diff --git a/reference/check_sce_layer.html b/reference/check_sce_layer.html
index e6129283..c926c5cf 100644
--- a/reference/check_sce_layer.html
+++ b/reference/check_sce_layer.html
@@ -64,7 +64,7 @@
Check input sce_layer
- Source: R/check_sce_layer.R
+ Source: R/check_sce_layer.R
check_sce_layer.Rd
@@ -112,8 +112,7 @@ Examples
## Obtain example data from the HumanPilot project
## (Maynard, Collado-Torres, et al, 2021)
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:55.536908 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:18.090538 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Check the pseudo-bulked data
check_sce_layer(sce_layer)
diff --git a/reference/check_spe.html b/reference/check_spe.html
index 00f18aab..262e37d5 100644
--- a/reference/check_spe.html
+++ b/reference/check_spe.html
@@ -64,7 +64,7 @@
@@ -123,8 +123,7 @@ Examples
## Check the object
check_spe(spe)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:56.493054 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:19.444343 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> class: SpatialExperiment
#> dim: 33538 47681
#> metadata(0):
diff --git a/reference/cluster_export.html b/reference/cluster_export.html
index 576e5969..41dcf6be 100644
--- a/reference/cluster_export.html
+++ b/reference/cluster_export.html
@@ -67,7 +67,7 @@
Export a column with cluster results
- Source: R/cluster_export.R
+ Source: R/cluster_export.R
cluster_export.Rd
@@ -134,8 +134,7 @@ Examples
cluster_export(spe, "spatialLIBD")
cluster_export(spe, "GraphBased")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:06.836252 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:34.076008 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
diff --git a/reference/cluster_import.html b/reference/cluster_import.html
index feed9a97..585bc91f 100644
--- a/reference/cluster_import.html
+++ b/reference/cluster_import.html
@@ -66,7 +66,7 @@
@@ -137,12 +137,11 @@ Examples
## Re-import them
colData(cluster_import(spe))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:17.501482 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:49.230922 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/spatialLIBD' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/spatialLIBD' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/GraphBased' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/GraphBased' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> DataFrame with 47681 rows and 71 columns
#> key sample_id Cluster sum_umi
diff --git a/reference/enough_ram.html b/reference/enough_ram.html
index 1aefe5c0..17fada89 100644
--- a/reference/enough_ram.html
+++ b/reference/enough_ram.html
@@ -63,7 +63,7 @@
Determine if you have enough RAM memory
- Source: R/enough_ram.R
+ Source: R/enough_ram.R
enough_ram.Rd
diff --git a/reference/fetch_data.html b/reference/fetch_data.html
index 860fcc8a..626b28ea 100644
--- a/reference/fetch_data.html
+++ b/reference/fetch_data.html
@@ -71,7 +71,7 @@
Download the Human DLPFC Visium data from LIBD
- Source: R/fetch_data.R
+ Source: R/fetch_data.R
fetch_data.Rd
@@ -166,8 +166,7 @@ Examples
## Download the SingleCellExperiment object
## at the layer-level
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:28.986594 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:04.599487 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Explore the data
sce_layer
diff --git a/reference/frame_limits.html b/reference/frame_limits.html
index 0a945d2b..ce67964f 100644
--- a/reference/frame_limits.html
+++ b/reference/frame_limits.html
@@ -73,7 +73,7 @@
@@ -154,8 +154,7 @@ Examples
## Obtain the frame limits for one sample
frame_limits(spe, sampleid = "151673")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:30.408348 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:07.106212 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> $y_min
#> [1] 64
#>
diff --git a/reference/gene_set_enrichment.html b/reference/gene_set_enrichment.html
index 58358fa3..69f114cc 100644
--- a/reference/gene_set_enrichment.html
+++ b/reference/gene_set_enrichment.html
@@ -68,7 +68,7 @@
Evaluate the enrichment for a list of gene sets
- Source: R/gene_set_enrichment.R
+ Source: R/gene_set_enrichment.R
gene_set_enrichment.Rd
@@ -176,8 +176,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:40.855511 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:21.075222 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/gene_set_enrichment_plot-1.png b/reference/gene_set_enrichment_plot-1.png
index d68b19ec..d366f433 100644
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diff --git a/reference/gene_set_enrichment_plot-2.png b/reference/gene_set_enrichment_plot-2.png
index 78df31f0..dbc691ef 100644
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diff --git a/reference/gene_set_enrichment_plot.html b/reference/gene_set_enrichment_plot.html
index 40392d13..ffdc11f2 100644
--- a/reference/gene_set_enrichment_plot.html
+++ b/reference/gene_set_enrichment_plot.html
@@ -64,7 +64,7 @@
Plot the gene set enrichment results
- Source: R/gene_set_enrichment_plot.R
+ Source: R/gene_set_enrichment_plot.R
gene_set_enrichment_plot.Rd
@@ -178,8 +178,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:41.867526 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:22.531835 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/geom_spatial-1.png b/reference/geom_spatial-1.png
index 64fd3d7a..946c446a 100644
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diff --git a/reference/geom_spatial.html b/reference/geom_spatial.html
index 5d50b49e..42e5c07c 100644
--- a/reference/geom_spatial.html
+++ b/reference/geom_spatial.html
@@ -66,7 +66,7 @@
A ggplot2 layer for visualizing the Visium histology
- Source: R/geom_spatial.R
+ Source: R/geom_spatial.R
geom_spatial.Rd
@@ -74,7 +74,7 @@ A ggplot2 layer for visualizing the Visium histology
This function defines a ggplot2::layer() for visualizing the histology
image from Visium. It can be combined with other ggplot2 functions for
visualizing the clusters as in vis_clus_p() or gene-level information
-as in vis_gene_p().
+as in vis_gene_p().
@@ -175,8 +175,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:43.207432 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:24.396394 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/get_colors.html b/reference/get_colors.html
index e49a44bf..dfbeb5c2 100644
--- a/reference/get_colors.html
+++ b/reference/get_colors.html
@@ -64,7 +64,7 @@
Obtain the colors for a set of cluster names
- Source: R/get_colors.R
+ Source: R/get_colors.R
get_colors.Rd
@@ -84,7 +84,7 @@ Arguments
- colors
A vector of colors. If NULL then a set of default colors will
be used when clusters has less than 12 unique values, otherwise
-Polychrome::palette36 will be used which can
+Polychrome::palette36 will be used which can
generate up to 36 unique colors. If the number of unique clusters is beyond
36 then this function will fail.
Examples
## Obtain the necessary data
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:54.433623 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:39.853193 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Example layer colors with the corresponding names
get_colors(libd_layer_colors, sce_layer$layer_guess)
diff --git a/reference/img_edit-1.png b/reference/img_edit-1.png
index 94154fc3..9af3f312 100644
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diff --git a/reference/img_edit.html b/reference/img_edit.html
index 9df344ec..004b6d82 100644
--- a/reference/img_edit.html
+++ b/reference/img_edit.html
@@ -65,7 +65,7 @@
@@ -222,8 +222,7 @@ Examples
x <- img_edit(spe, sampleid = "151507", brightness = 25)
plot(x)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:56.683064 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:41.084926 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/img_update.html b/reference/img_update.html
index 5b6a0f39..5d92fe1f 100644
--- a/reference/img_update.html
+++ b/reference/img_update.html
@@ -63,7 +63,7 @@
@@ -139,8 +139,7 @@ Examples
## Reduce brightness to 25% and update the imgData()
imgData(img_update(spe, sampleid = "151507", brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:07.614049 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:56.77859 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/img_update_all.html b/reference/img_update_all.html
index e322e40f..8a0c7996 100644
--- a/reference/img_update_all.html
+++ b/reference/img_update_all.html
@@ -65,7 +65,7 @@
Update the images for all samples
- Source: R/img_update_all.R
+ Source: R/img_update_all.R
img_update_all.Rd
@@ -138,8 +138,7 @@ Examples
## update the imgData()
imgData(img_update_all(spe, brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:17.633699 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:11.011904 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 24 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/index.html b/reference/index.html
index 3d629a4c..fdcce2ae 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -249,6 +249,10 @@ All functions vis_gene()
Sample spatial gene visualization
+
+
+ Sample spatial gene visualization workhorse function
diff --git a/reference/layer_boxplot-1.png b/reference/layer_boxplot-1.png
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diff --git a/reference/layer_boxplot.html b/reference/layer_boxplot.html
index 90de61cd..302acf11 100644
--- a/reference/layer_boxplot.html
+++ b/reference/layer_boxplot.html
@@ -65,7 +65,7 @@
Layer-level (group-level) boxplots
- Source: R/layer_boxplot.R
+ Source: R/layer_boxplot.R
layer_boxplot.Rd
@@ -185,11 +185,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:28.442408 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:28.503014 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:29.096088 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:29.384093 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Top 2 genes from the enrichment model
sig_genes <- sig_genes_extract_all(
diff --git a/reference/layer_matrix_plot-1.png b/reference/layer_matrix_plot-1.png
index d9460395..4f269d7a 100644
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diff --git a/reference/layer_matrix_plot-2.png b/reference/layer_matrix_plot-2.png
index 8e3e7d6d..2f29029a 100644
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diff --git a/reference/layer_matrix_plot.html b/reference/layer_matrix_plot.html
index d2728bb4..d5cd6750 100644
--- a/reference/layer_matrix_plot.html
+++ b/reference/layer_matrix_plot.html
@@ -66,7 +66,7 @@
Visualize a matrix of values across human brain layers
- Source: R/layer_matrix_plot.R
+ Source: R/layer_matrix_plot.R
layer_matrix_plot.Rd
diff --git a/reference/layer_stat_cor.html b/reference/layer_stat_cor.html
index be43eee0..208b193a 100644
--- a/reference/layer_stat_cor.html
+++ b/reference/layer_stat_cor.html
@@ -63,7 +63,7 @@
Layer modeling correlation of statistics
- Source: R/layer_stat_cor.R
+ Source: R/layer_stat_cor.R
layer_stat_cor.Rd
@@ -156,8 +156,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:31.53213 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
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## Compute the correlations
cor_stats_layer <- layer_stat_cor(
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index 2e2b880f..a6ca399d 100644
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diff --git a/reference/layer_stat_cor_plot.html b/reference/layer_stat_cor_plot.html
index d08a54a2..7670f03a 100644
--- a/reference/layer_stat_cor_plot.html
+++ b/reference/layer_stat_cor_plot.html
@@ -66,7 +66,7 @@
Visualize the layer modeling correlation of statistics
- Source: R/layer_stat_cor_plot.R
+ Source: R/layer_stat_cor_plot.R
layer_stat_cor_plot.Rd
@@ -145,8 +145,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:32.436771 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:33.883339 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/libd_layer_colors.html b/reference/libd_layer_colors.html
index d2df282e..6a843fec 100644
--- a/reference/libd_layer_colors.html
+++ b/reference/libd_layer_colors.html
@@ -64,7 +64,7 @@
diff --git a/reference/locate_images.html b/reference/locate_images.html
index 62727198..8cbe293c 100644
--- a/reference/locate_images.html
+++ b/reference/locate_images.html
@@ -65,7 +65,7 @@
diff --git a/reference/multi_gene_pca.html b/reference/multi_gene_pca.html
index 58575a98..334fbe7d 100644
--- a/reference/multi_gene_pca.html
+++ b/reference/multi_gene_pca.html
@@ -68,7 +68,7 @@
Combine multiple continuous variables through PCA
- Source: R/multi_gene_pca.R
+ Source: R/multi_gene_pca.R
multi_gene_pca.Rd
diff --git a/reference/multi_gene_sparsity.html b/reference/multi_gene_sparsity.html
index 042ec2af..2ababa43 100644
--- a/reference/multi_gene_sparsity.html
+++ b/reference/multi_gene_sparsity.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by proportion of positive values
- Source: R/multi_gene_sparsity.R
+ Source: R/multi_gene_sparsity.R
multi_gene_sparsity.Rd
diff --git a/reference/multi_gene_z_score.html b/reference/multi_gene_z_score.html
index 612273f5..ce8a878a 100644
--- a/reference/multi_gene_z_score.html
+++ b/reference/multi_gene_z_score.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by averaging Z scores
- Source: R/multi_gene_z_score.R
+ Source: R/multi_gene_z_score.R
multi_gene_z_score.Rd
diff --git a/reference/prep_stitched_data.html b/reference/prep_stitched_data.html
index 0c4a592e..36678e3a 100644
--- a/reference/prep_stitched_data.html
+++ b/reference/prep_stitched_data.html
@@ -68,7 +68,7 @@
Prepare stitched data for plotting
- Source: R/prep_stitched_data.R
+ Source: R/prep_stitched_data.R
prep_stitched_data.Rd
diff --git a/reference/read10xVisiumAnalysis.html b/reference/read10xVisiumAnalysis.html
index b36ef451..7e04bd5b 100644
--- a/reference/read10xVisiumAnalysis.html
+++ b/reference/read10xVisiumAnalysis.html
@@ -64,7 +64,7 @@
Load analysis data from a 10x Genomics Visium experiment
- Source: R/read10xVisiumAnalysis.R
+ Source: R/read10xVisiumAnalysis.R
read10xVisiumAnalysis.Rd
@@ -118,7 +118,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/read10xVisiumWrapper.html b/reference/read10xVisiumWrapper.html
index 56b267a0..c8d01991 100644
--- a/reference/read10xVisiumWrapper.html
+++ b/reference/read10xVisiumWrapper.html
@@ -66,7 +66,7 @@
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
- Source: R/read10xVisiumWrapper.R
+ Source: R/read10xVisiumWrapper.R
read10xVisiumWrapper.Rd
@@ -162,7 +162,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/registration_block_cor.html b/reference/registration_block_cor.html
index 33000024..126fabd2 100644
--- a/reference/registration_block_cor.html
+++ b/reference/registration_block_cor.html
@@ -66,7 +66,7 @@
Spatial registration: block correlation
- Source: R/registration_block_cor.R
+ Source: R/registration_block_cor.R
registration_block_cor.Rd
@@ -121,36 +121,36 @@ See also
Examples
example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:34.847415 make pseudobulk object
-#> 2024-07-16 17:02:34.953364 drop lowly expressed genes
-#> 2024-07-16 17:02:34.99097 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:37.088175 make pseudobulk object
+#> 2024-07-17 13:51:37.267087 drop lowly expressed genes
+#> 2024-07-17 13:51:37.336566 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -179,10 +179,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:35.032307 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:37.415555 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -198,8 +198,8 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:35.038484 run duplicateCorrelation()
-#> 2024-07-16 17:02:35.564971 The estimated correlation is: -0.0187869166526901
+#> 2024-07-17 13:51:37.428263 run duplicateCorrelation()
+#> 2024-07-17 13:51:38.691552 The estimated correlation is: -0.0187869166526901
diff --git a/reference/registration_model.html b/reference/registration_model.html
index 7a26252f..c96dc0da 100644
--- a/reference/registration_model.html
+++ b/reference/registration_model.html
@@ -67,7 +67,7 @@
Spatial registration: model
- Source: R/registration_model.R
+ Source: R/registration_model.R
registration_model.Rd
@@ -125,34 +125,34 @@ See also
Examples
example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:35.873124 make pseudobulk object
-#> 2024-07-16 17:02:35.960837 drop lowly expressed genes
-#> 2024-07-16 17:02:35.986325 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:39.129951 make pseudobulk object
+#> 2024-07-17 13:51:39.31554 drop lowly expressed genes
+#> 2024-07-17 13:51:39.370617 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -181,7 +181,7 @@ Examples
#> D_S S D 14
#> E_S S E 11
registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:36.024617 create model matrix
+#> 2024-07-17 13:51:39.447064 create model matrix
head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
diff --git a/reference/registration_pseudobulk.html b/reference/registration_pseudobulk.html
index 653d03b2..8722ef39 100644
--- a/reference/registration_pseudobulk.html
+++ b/reference/registration_pseudobulk.html
@@ -64,7 +64,7 @@
Spatial registration: pseudobulk
- Source: R/registration_pseudobulk.R
+ Source: R/registration_pseudobulk.R
registration_pseudobulk.Rd
@@ -159,9 +159,9 @@ Examples
## Pseudo-bulk
sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.341187 make pseudobulk object
-#> 2024-07-16 17:02:36.4321 drop lowly expressed genes
-#> 2024-07-16 17:02:36.458483 normalize expression
+#> 2024-07-17 13:51:39.903902 make pseudobulk object
+#> 2024-07-17 13:51:40.056716 drop lowly expressed genes
+#> 2024-07-17 13:51:40.111023 normalize expression
colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
diff --git a/reference/registration_stats_anova.html b/reference/registration_stats_anova.html
index 1cf15645..cdc9d765 100644
--- a/reference/registration_stats_anova.html
+++ b/reference/registration_stats_anova.html
@@ -66,7 +66,7 @@
Spatial registration: compute ANOVA statistics
- Source: R/registration_stats_anova.R
+ Source: R/registration_stats_anova.R
registration_stats_anova.Rd
@@ -153,38 +153,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.908 make pseudobulk object
-#> 2024-07-16 17:02:36.981269 drop lowly expressed genes
-#> 2024-07-16 17:02:37.007143 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:40.701746 make pseudobulk object
+#> 2024-07-17 13:51:40.884268 drop lowly expressed genes
+#> 2024-07-17 13:51:40.939518 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -213,10 +213,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:37.061168 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:41.012467 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -232,14 +232,14 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:37.066375 run duplicateCorrelation()
-#> 2024-07-16 17:02:37.583667 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:41.024125 run duplicateCorrelation()
+#> 2024-07-17 13:51:42.289985 The estimated correlation is: -0.0187869166526901
results_anova <- registration_stats_anova(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.589856 computing F-statistics
+#> 2024-07-17 13:51:42.302664 computing F-statistics
head(results_anova)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1328075 0.93918553 0.9951876 5.499488 ENSG1 gene1
@@ -254,7 +254,7 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.615244 computing F-statistics
+#> 2024-07-17 13:51:42.365534 computing F-statistics
head(results_anova_nan)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1357180 0.93736053 0.9943765 5.499488 ENSG1 gene1
@@ -276,7 +276,7 @@ Examples
covars = NULL,
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "nocovar"
)
-#> 2024-07-16 17:02:37.632809 computing F-statistics
+#> 2024-07-17 13:51:42.415614 computing F-statistics
head(results_anova_nocovar)
#> f_stat_nocovar p_value_nocovar fdr_nocovar AveExpr_nocovar ensembl gene
#> 1 0.1393641 0.9351345 0.9962097 5.499488 ENSG1 gene1
diff --git a/reference/registration_stats_enrichment.html b/reference/registration_stats_enrichment.html
index c2fc717e..b97c7f9c 100644
--- a/reference/registration_stats_enrichment.html
+++ b/reference/registration_stats_enrichment.html
@@ -65,7 +65,7 @@
Spatial registration: compute enrichment statistics
- Source: R/registration_stats_enrichment.R
+ Source: R/registration_stats_enrichment.R
registration_stats_enrichment.Rd
@@ -144,38 +144,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:37.992936 make pseudobulk object
-#> 2024-07-16 17:02:38.06571 drop lowly expressed genes
-#> 2024-07-16 17:02:38.091375 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:42.992514 make pseudobulk object
+#> 2024-07-17 13:51:43.146693 drop lowly expressed genes
+#> 2024-07-17 13:51:43.201202 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -204,10 +204,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:38.129501 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:43.274381 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -223,15 +223,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:38.134799 run duplicateCorrelation()
-#> 2024-07-16 17:02:38.654908 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:43.285637 run duplicateCorrelation()
+#> 2024-07-17 13:51:44.583617 The estimated correlation is: -0.0187869166526901
results_enrichment <- registration_stats_enrichment(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.657236 computing enrichment statistics
-#> 2024-07-16 17:02:38.701689 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.587859 computing enrichment statistics
+#> 2024-07-17 13:51:44.705956 extract and reformat enrichment results
head(results_enrichment)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1482017 0.5610669 -0.3612235 -0.3458508 0.88374480 0.58130631
@@ -260,8 +260,8 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.712787 computing enrichment statistics
-#> 2024-07-16 17:02:38.771541 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.739083 computing enrichment statistics
+#> 2024-07-17 13:51:44.842281 extract and reformat enrichment results
head(results_enrichment_nan)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1497747 0.56711100 -0.3650801 -0.3495404 0.88252049 0.57727506
diff --git a/reference/registration_stats_pairwise.html b/reference/registration_stats_pairwise.html
index c11a5e44..03bff131 100644
--- a/reference/registration_stats_pairwise.html
+++ b/reference/registration_stats_pairwise.html
@@ -66,7 +66,7 @@
Spatial registration: compute pairwise statistics
- Source: R/registration_stats_pairwise.R
+ Source: R/registration_stats_pairwise.R
registration_stats_pairwise.Rd
@@ -146,38 +146,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:39.085978 make pseudobulk object
-#> 2024-07-16 17:02:39.159736 drop lowly expressed genes
-#> 2024-07-16 17:02:39.185678 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:45.303165 make pseudobulk object
+#> 2024-07-17 13:51:45.456984 drop lowly expressed genes
+#> 2024-07-17 13:51:45.511196 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -206,10 +206,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:39.224065 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:45.621594 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -225,15 +225,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:39.22931 run duplicateCorrelation()
-#> 2024-07-16 17:02:39.781072 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:45.632849 run duplicateCorrelation()
+#> 2024-07-17 13:51:46.88774 The estimated correlation is: -0.0187869166526901
results_pairwise <- registration_stats_pairwise(sce_pseudo,
registration_mod, block_cor,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.782515 running the baseline pairwise model
-#> 2024-07-16 17:02:39.790292 computing pairwise statistics
+#> 2024-07-17 13:51:46.889688 running the baseline pairwise model
+#> 2024-07-17 13:51:46.906431 computing pairwise statistics
head(results_pairwise)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2393683 0.29771391 0.28880637 0.5370822 0.5281747
@@ -277,8 +277,8 @@ Examples
block_cor = NaN,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.811874 running the baseline pairwise model
-#> 2024-07-16 17:02:39.818697 computing pairwise statistics
+#> 2024-07-17 13:51:46.971696 running the baseline pairwise model
+#> 2024-07-17 13:51:46.989106 computing pairwise statistics
head(results_pairwise_nan)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2419770 0.30095840 0.29195379 0.5429354 0.5339308
diff --git a/reference/registration_wrapper.html b/reference/registration_wrapper.html
index 546b32eb..a04252d2 100644
--- a/reference/registration_wrapper.html
+++ b/reference/registration_wrapper.html
@@ -68,7 +68,7 @@
Spatial registration: wrapper function
- Source: R/registration_wrapper.R
+ Source: R/registration_wrapper.R
registration_wrapper.Rd
@@ -200,18 +200,18 @@ Examples
sce,
"Cell_Cycle", "sample_id", c("age"), "ensembl", "gene_name", "wrapper"
)
-#> 2024-07-16 17:02:40.149028 make pseudobulk object
-#> 2024-07-16 17:02:40.221379 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:02:40.231996 drop lowly expressed genes
-#> 2024-07-16 17:02:40.27465 normalize expression
-#> 2024-07-16 17:02:40.303232 create model matrix
-#> 2024-07-16 17:02:40.308019 run duplicateCorrelation()
-#> 2024-07-16 17:02:41.300298 The estimated correlation is: -0.0783081238514527
-#> 2024-07-16 17:02:41.301437 computing enrichment statistics
-#> 2024-07-16 17:02:41.342436 extract and reformat enrichment results
-#> 2024-07-16 17:02:41.35071 running the baseline pairwise model
-#> 2024-07-16 17:02:41.357315 computing pairwise statistics
-#> 2024-07-16 17:02:41.380689 computing F-statistics
+#> 2024-07-17 13:51:47.541862 make pseudobulk object
+#> 2024-07-17 13:51:47.707925 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:51:47.729853 drop lowly expressed genes
+#> 2024-07-17 13:51:47.785167 normalize expression
+#> 2024-07-17 13:51:47.8429 create model matrix
+#> 2024-07-17 13:51:47.853499 run duplicateCorrelation()
+#> 2024-07-17 13:51:50.267571 The estimated correlation is: -0.0783081238514532
+#> 2024-07-17 13:51:50.269845 computing enrichment statistics
+#> 2024-07-17 13:51:50.386595 extract and reformat enrichment results
+#> 2024-07-17 13:51:50.412505 running the baseline pairwise model
+#> 2024-07-17 13:51:50.430847 computing pairwise statistics
+#> 2024-07-17 13:51:50.505218 computing F-statistics
diff --git a/reference/run_app.html b/reference/run_app.html
index d23cb924..2cca4ddc 100644
--- a/reference/run_app.html
+++ b/reference/run_app.html
@@ -65,7 +65,7 @@
@@ -270,7 +270,7 @@ Examples
vars <- colnames(colData(spe))
## Set default cluster colors
- colors_BayesSpace <- Polychrome::palette36.colors(28)
+ colors_BayesSpace <- Polychrome::palette36.colors(28)
names(colors_BayesSpace) <- c(1:28)
m <- match(as.character(spe$BayesSpace_harmony_09), names(colors_BayesSpace))
stopifnot(all(!is.na(m)))
diff --git a/reference/sce_to_spe.html b/reference/sce_to_spe.html
index 84fd3093..e0797fb6 100644
--- a/reference/sce_to_spe.html
+++ b/reference/sce_to_spe.html
@@ -67,7 +67,7 @@
@@ -127,8 +127,7 @@ Examples
## Transform it to a SpatialExperiment object
spe <- sce_to_spe(sce)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:43.103369 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:52.727073 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/sig_genes_extract.html b/reference/sig_genes_extract.html
index 0ecdbcc3..4c448c85 100644
--- a/reference/sig_genes_extract.html
+++ b/reference/sig_genes_extract.html
@@ -67,7 +67,7 @@
Extract significant genes
- Source: R/sig_genes_extract.R
+ Source: R/sig_genes_extract.R
sig_genes_extract.Rd
@@ -156,11 +156,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:52.484674 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:05.714888 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:53.182388 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:06.659035 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## anova top 10 genes
sig_genes_extract(
diff --git a/reference/sig_genes_extract_all.html b/reference/sig_genes_extract_all.html
index 17516a57..4a42f61e 100644
--- a/reference/sig_genes_extract_all.html
+++ b/reference/sig_genes_extract_all.html
@@ -65,7 +65,7 @@
Extract significant genes for all modeling results
- Source: R/sig_genes_extract_all.R
+ Source: R/sig_genes_extract_all.R
sig_genes_extract_all.Rd
@@ -128,11 +128,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.422915 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:10.311903 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.970561 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:11.371345 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## top 10 genes for all models
sig_genes_extract_all(
diff --git a/reference/sort_clusters.html b/reference/sort_clusters.html
index 8dccd3d7..675c4397 100644
--- a/reference/sort_clusters.html
+++ b/reference/sort_clusters.html
@@ -65,7 +65,7 @@
diff --git a/reference/spatialLIBD-package.html b/reference/spatialLIBD-package.html
index 148e52f3..c22a18c2 100644
--- a/reference/spatialLIBD-package.html
+++ b/reference/spatialLIBD-package.html
@@ -64,7 +64,7 @@
spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
- Source: R/spatialLIBD-package.R
+ Source: R/spatialLIBD-package.R
spatialLIBD-package.Rd
diff --git a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
index e6a4ba86..4dbbeb2a 100644
--- a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
+++ b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
@@ -69,7 +69,7 @@
Cell cluster t-statistics from Tran et al
- Source: R/data.R
+ Source: R/data.R
tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.Rd
diff --git a/reference/vis_clus-1.png b/reference/vis_clus-1.png
index b62ae3bc..fff9298e 100644
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diff --git a/reference/vis_clus-2.png b/reference/vis_clus-2.png
index 59f18aa4..4962aaef 100644
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diff --git a/reference/vis_clus-3.png b/reference/vis_clus-3.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus-4.png b/reference/vis_clus-4.png
index 7a08ba8a..fd74eca4 100644
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diff --git a/reference/vis_clus.html b/reference/vis_clus.html
index 4c441931..29b47fed 100644
--- a/reference/vis_clus.html
+++ b/reference/vis_clus.html
@@ -65,7 +65,7 @@
@@ -242,8 +242,7 @@ Examples
)
print(p4)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:52:14.053539 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_clus_p-1.png b/reference/vis_clus_p-1.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus_p.html b/reference/vis_clus_p.html
index 0106b4be..1e416396 100644
--- a/reference/vis_clus_p.html
+++ b/reference/vis_clus_p.html
@@ -66,7 +66,7 @@
Sample spatial cluster visualization workhorse function
- Source: R/vis_clus_p.R
+ Source: R/vis_clus_p.R
vis_clus_p.Rd
@@ -74,7 +74,7 @@ Sample spatial cluster visualization workhorse function
This function visualizes the clusters for one given sample at the spot-level
using (by default) the histology information on the background. This is the
function that does all the plotting behind vis_clus(). To visualize
-gene-level (or any continuous variable) use vis_gene_p().
+gene-level (or any continuous variable) use vis_gene_p().
@@ -202,8 +202,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:52:33.265544 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene-1.png b/reference/vis_gene-1.png
index dd3f3f08..3585ea9b 100644
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diff --git a/reference/vis_gene-10.png b/reference/vis_gene-10.png
index fe1916ef..a44ac448 100644
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diff --git a/reference/vis_gene-2.png b/reference/vis_gene-2.png
index e31f94d3..7da9ccfd 100644
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diff --git a/reference/vis_gene-3.png b/reference/vis_gene-3.png
index ad0dd5f5..e4286c69 100644
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diff --git a/reference/vis_gene-4.png b/reference/vis_gene-4.png
index 55d24ff4..1ff3e170 100644
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diff --git a/reference/vis_gene-5.png b/reference/vis_gene-5.png
index c1e58e44..6cbbe839 100644
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diff --git a/reference/vis_gene-6.png b/reference/vis_gene-6.png
index 528c1c2a..9eccafab 100644
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diff --git a/reference/vis_gene-7.png b/reference/vis_gene-7.png
index da60a0bf..c26013a0 100644
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diff --git a/reference/vis_gene-8.png b/reference/vis_gene-8.png
index 2e73ba4d..a91893cf 100644
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diff --git a/reference/vis_gene-9.png b/reference/vis_gene-9.png
index 9123b986..fa2c6a94 100644
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diff --git a/reference/vis_gene.html b/reference/vis_gene.html
index e39667fc..f0e49f68 100644
--- a/reference/vis_gene.html
+++ b/reference/vis_gene.html
@@ -66,7 +66,7 @@
@@ -220,12 +220,12 @@ Value
Details
This function subsets spe to the given sample and prepares the
-data and title for vis_gene_p(). It also adds a caption to the plot.
+data and title for vis_gene_p(). It also adds a caption to the plot.
See also
Other Spatial gene visualization functions:
-vis_gene_p(),
+vis_gene_p(),
vis_grid_gene()
@@ -341,8 +341,7 @@ Examples
)
print(p8)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:22.728238 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:48.10019 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene_p-1.png b/reference/vis_gene_p-1.png
new file mode 100644
index 00000000..24287b46
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diff --git a/reference/vis_gene_p.html b/reference/vis_gene_p.html
new file mode 100644
index 00000000..4f32d6a8
--- /dev/null
+++ b/reference/vis_gene_p.html
@@ -0,0 +1,245 @@
+
+Sample spatial gene visualization workhorse function — vis_gene_p • spatialLIBD
+
+
+
+
+
+
+
+
+
+
+
+
+ This function visualizes the gene expression stored in assays(spe) or any
+continuous variable stored in colData(spe) for one given sample at the
+spot-level using (by default) the histology information on the background.
+This is the function that does all the plotting behind vis_gene()
+To visualize clusters (or any discrete variable) use vis_clus_p().
+
+
+
+ vis_gene_p(
+ spe,
+ d,
+ sampleid = unique(spe$sample_id)[1],
+ spatial,
+ title,
+ viridis = TRUE,
+ image_id = "lowres",
+ alpha = NA,
+ cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4",
+ "springgreen", "goldenrod", "red"),
+ point_size = 2,
+ auto_crop = TRUE,
+ na_color = "#CCCCCC40",
+ legend_title = ""
+)
+
+
+
+ Arguments
+
+
+- spe
+A
+SpatialExperiment-class
+object. See fetch_data() for how to download some example objects or
+read10xVisiumWrapper() to read in spaceranger --count output files and
+build your own spe object.
- d
+A data.frame() with the sample-level information. This is
+typically obtained using cbind(colData(spe), spatialCoords(spe)).
+The data.frame has to contain
+a column with the continuous variable data to plot stored under d$COUNT.
- sampleid
+A character(1) specifying which sample to plot from
+colData(spe)$sample_id (formerly colData(spe)$sample_name).
- spatial
+A logical(1) indicating whether to include the histology
+layer from geom_spatial(). If you plan to use
+ggplotly() then it's best to set this to FALSE.
- title
+The title for the plot.
- viridis
+A logical(1) whether to use the color-blind friendly
+palette from viridis or the color palette used
+in the paper that was chosen for contrast when visualizing the data on
+top of the histology image. One issue is being able to differentiate low
+values from NA ones due to the purple-ish histology information that is
+dependent on cell density.
- image_id
+A character(1) with the name of the image ID you want to
+use in the background.
- alpha
+A numeric(1) in the [0, 1] range that specifies the
+transparency level of the data on the spots.
- cont_colors
+A character() vector of colors that supersedes the
+viridis argument.
- point_size
+A numeric(1) specifying the size of the points. Defaults
+to 1.25. Some colors look better if you use 2 for instance.
- auto_crop
+A logical(1) indicating whether to automatically crop
+the image / plotting area, which is useful if the Visium capture area is
+not centered on the image and if the image is not a square.
- na_color
+A character(1) specifying a color for the NA values.
+If you set alpha = NA then it's best to set na_color to a color that has
+alpha blending already, which will make non-NA values pop up more and the NA
+values will show with a lighter color. This behavior is lost when alpha is
+set to a non-NA value.
- legend_title
+A character(1) specifying the legend title.
+
+ Value
+ A ggplot2 object.
+
+
+ See also
+ Other Spatial gene visualization functions:
+vis_gene(),
+vis_grid_gene()
+
+
+
+ Examples
+
+if (enough_ram()) {
+ ## Obtain the necessary data
+ if (!exists("spe")) spe <- fetch_data("spe")
+
+ ## Prepare the data for the plotting function
+ spe_sub <- spe[, spe$sample_id == "151673"]
+ df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
+ df$COUNT <- df$expr_chrM_ratio
+
+ ## Don't plot the histology information
+ p <- vis_gene_p(
+ spe = spe_sub,
+ d = df,
+ sampleid = "151673",
+ title = "151673 chrM expr ratio",
+ spatial = FALSE
+ )
+ print(p)
+
+ ## Clean up
+ rm(spe_sub)
+}
+#> 2024-07-17 13:53:14.003193 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/reference/vis_grid_clus-1.png b/reference/vis_grid_clus-1.png
index fc3c2d6c..ea564e20 100644
Binary files a/reference/vis_grid_clus-1.png and b/reference/vis_grid_clus-1.png differ
diff --git a/reference/vis_grid_clus.html b/reference/vis_grid_clus.html
index beb4cdd7..a1aec073 100644
--- a/reference/vis_grid_clus.html
+++ b/reference/vis_grid_clus.html
@@ -65,7 +65,7 @@
Sample spatial cluster visualization grid
- Source: R/vis_grid_clus.R
+ Source: R/vis_grid_clus.R
vis_grid_clus.Rd
@@ -237,8 +237,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:41.57373 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:29.053452 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_grid_gene-1.png b/reference/vis_grid_gene-1.png
index d8f795d8..b246fec3 100644
Binary files a/reference/vis_grid_gene-1.png and b/reference/vis_grid_gene-1.png differ
diff --git a/reference/vis_grid_gene.html b/reference/vis_grid_gene.html
index f5428110..7f5c56b0 100644
--- a/reference/vis_grid_gene.html
+++ b/reference/vis_grid_gene.html
@@ -66,7 +66,7 @@
Sample spatial gene visualization grid
- Source: R/vis_grid_gene.R
+ Source: R/vis_grid_gene.R
vis_grid_gene.Rd
@@ -234,7 +234,7 @@ Details
See also
Other Spatial gene visualization functions:
vis_gene(),
-vis_gene_p()
+vis_gene_p()
@@ -256,8 +256,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:53.38865 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:45.486537 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/sitemap.xml b/sitemap.xml
index d4f77066..8a33c15f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -62,6 +62,7 @@
/reference/vis_clus.html /reference/vis_clus_p.html /reference/vis_gene.html /reference/vis_gene_p.html /reference/vis_grid_clus.html /reference/vis_grid_gene.html
## Run our shiny app
if (interactive()) {
@@ -1116,200 +1114,202 @@ Reproducibilitylibrary("knitr")
knit("TenX_data_download.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2024-07-16 17:06:32 EDT"#> [1] "2024-07-17 13:57:48 UTC"Wallclock time spent generating the vignette.
-#> Time difference of 1.183 mins#> Time difference of 1.705 minsR session information.
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
#>
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#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────Bibliography[5] A. Oleś. BiocStyle: Standard styles for vignettes and other -Bioconductor documents. R package version 2.32.1. 2024. URL: -https://github.com/Bioconductor/BiocStyle. +Bioconductor documents. R package version 2.32.1. 2024. DOI: +10.18129/B9.bioc.BiocStyle. +URL: +https://bioconductor.org/packages/BiocStyle.
[6]
@@ -1385,13 +1387,16 @@ Bibliography[9]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.12.0. 2024.
+Sessions. R package version 2.12.0. 2024. DOI:
+10.18129/B9.bioc.BiocFileCache.
+URL:
+https://bioconductor.org/packages/BiocFileCache.
[10] H. Wickham. lobstr: Visualize R Data Structures with Trees. R -package version 1.1.2. 2022. URL: -https://CRAN.R-project.org/package=lobstr. +package version 1.1.2, https://github.com/r-lib/lobstr. 2022. URL: +https://lobstr.r-lib.org/.
[11]
@@ -1402,8 +1407,8 @@ Bibliography[12]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[13]
diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-1.png b/articles/TenX_data_download_files/figure-html/test_visualizations-1.png
index befc0397..681004b2 100644
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diff --git a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png
index 017fcd18..ac8b5fff 100644
Binary files a/articles/TenX_data_download_files/figure-html/test_visualizations-2.png and b/articles/TenX_data_download_files/figure-html/test_visualizations-2.png differ
diff --git a/articles/guide_to_spatial_registration.html b/articles/guide_to_spatial_registration.html
index a056ae9f..cb254465 100644
--- a/articles/guide_to_spatial_registration.html
+++ b/articles/guide_to_spatial_registration.html
@@ -101,9 +101,9 @@ Date the vignette was generated. Wallclock time spent generating the vignette.Louise
Development
lahuuki@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/guide_to_spatial_registration.Rmd
+ Source: vignettes/guide_to_spatial_registration.Rmd
guide_to_spatial_registration.RmdLoad required packages
library("spatialLIBD")
-#> Warning: package 'S4Vectors' was built under R version 4.4.1
-#> Warning: package 'IRanges' was built under R version 4.4.1
library("SingleCellExperiment")Spatial Reference
+#> 2024-07-17 13:54:21.031386 make pseudobulk object
+#> 2024-07-17 13:54:22.727446 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:54:22.789323 drop lowly expressed genes
+#> 2024-07-17 13:54:22.963372 normalize expression
+#> 2024-07-17 13:54:24.427132 create model matrix
+#> 2024-07-17 13:54:24.451001 run duplicateCorrelation()
+#> 2024-07-17 13:54:37.623842 The estimated correlation is: 0.138734774807097
+#> 2024-07-17 13:54:37.626295 computing enrichment statistics
+#> 2024-07-17 13:54:38.79442 extract and reformat enrichment results
+#> 2024-07-17 13:54:38.851417 running the baseline pairwise model
+#> 2024-07-17 13:54:39.041435 computing pairwise statistics
+#> 2024-07-17 13:54:40.421524 computing F-statistics
## get reference layer enrichment statistics
layer_modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:13.829724 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:54:13.294755 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
layer_modeling_results$enrichment[1:5, 1:5]
#> t_stat_WM t_stat_Layer1 t_stat_Layer2 t_stat_Layer3 t_stat_Layer4
@@ -393,18 +391,18 @@ Get Enrichment statistics
gene_ensembl = "gene_id",
gene_name = "gene_name"
)
-#> 2024-07-16 17:04:17.342908 make pseudobulk object
-#> 2024-07-16 17:04:18.696265 dropping 13 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:04:18.724833 drop lowly expressed genes
-#> 2024-07-16 17:04:18.799779 normalize expression
-#> 2024-07-16 17:04:19.584255 create model matrix
-#> 2024-07-16 17:04:19.595618 run duplicateCorrelation()
-#> 2024-07-16 17:04:25.229344 The estimated correlation is: 0.138734774807097
-#> 2024-07-16 17:04:25.231011 computing enrichment statistics
-#> 2024-07-16 17:04:25.960375 extract and reformat enrichment results
-#> 2024-07-16 17:04:26.003855 running the baseline pairwise model
-#> 2024-07-16 17:04:26.12952 computing pairwise statistics
-#> 2024-07-16 17:04:27.403954 computing F-statistics
Extract Enrichment t-statistics
@@ -564,187 +562,189 @@
Reproducibilitylibrary("knitr")
knit("guide_to_spatial_registration.Rmd", tangle = TRUE)
+#> [1] "2024-07-16 17:04:28 EDT"#> [1] "2024-07-17 13:54:41 UTC"
+#> Time difference of 21.924 secs#> Time difference of 40.965 secsR session information.
@@ -782,8 +782,10 @@ #> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
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#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────Bibliography[4]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.32.1. 2024. URL:
-https://github.com/Bioconductor/BiocStyle.
+Bioconductor documents. R package version 2.32.1. 2024. DOI:
+10.18129/B9.bioc.BiocStyle.
+URL:
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[5]
@@ -817,8 +819,8 @@ Bibliography[9]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[10]
diff --git a/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png b/articles/guide_to_spatial_registration_files/figure-html/layer_cor_plot-1.png
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diff --git a/articles/multi_gene_plots.html b/articles/multi_gene_plots.html
index 684a2bbb..847ca6a7 100644
--- a/articles/multi_gene_plots.html
+++ b/articles/multi_gene_plots.html
@@ -108,9 +108,9 @@ Date the vignette was generated. Wallclock time spent generating the vignette. Once you have downloaded the objects, we can explore them a little
bit As of version 1.3.3, spatialLIBD
supports the Date the vignette was generated. Wallclock time spent generating the vignette.Leonardo
Public Health
lcolladotor@gmail.com
- 16 July 2024
+ 17 July 2024
- Source: vignettes/multi_gene_plots.Rmd
+ Source: vignettes/multi_gene_plots.Rmd
multi_gene_plots.RmdPlotting One Gene
modeling_results <- fetch_data(type = "modeling_results")
-#> 2024-07-16 17:04:43.021669 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:06.762958 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
sce_layer <- fetch_data(type = "sce_layer")
-#> 2024-07-16 17:04:43.645201 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:07.675711 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
sig_genes <- sig_genes_extract_all(
n = 400,
modeling_results = modeling_results,
@@ -421,189 +421,191 @@ Reproducibilitylibrary("knitr")
knit("multi_gene_plots.Rmd", tangle = TRUE)
+#> [1] "2024-07-16 17:04:53 EDT"#> [1] "2024-07-17 13:55:23 UTC"
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diff --git a/articles/spatialLIBD.html b/articles/spatialLIBD.html
index 241db4f0..3e707196 100644
--- a/articles/spatialLIBD.html
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#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────Andrew E.
Campus
andrew.jaffe@libd.org
- 16 July 2024
+ 17 July 2024
- Source: vignettes/spatialLIBD.Rmd
+ Source: vignettes/spatialLIBD.Rmd
spatialLIBD.RmdDownloading the data with
s
## Download the small example sce data
sce <- fetch_data(type = "sce_example", eh = ehub)
-#> 2024-07-16 17:05:03.908351 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:39.830372 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
## Convert to a SpatialExperiment object
spe <- sce_to_spe(sce)
@@ -426,9 +426,9 @@ Downloading the data with
s
## Query ExperimentHub and download the data
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer", eh = ehub)
-#> 2024-07-16 17:05:07.931392 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:55:44.107964 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
modeling_results <- fetch_data("modeling_results", eh = ehub)
-#> 2024-07-16 17:05:08.248131 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
@@ -501,7 +501,7 @@
Downloading the data with
s
)
)
#> user system elapsed
-#> 5.090 0.218 5.325
+#> 9.944 0.296 10.247
## Explore the result
class(sig_genes)
@@ -707,7 +707,7 @@ Spot-level genes and continuo
the histology set of purple tones that are noticeable when the
continuous variable is below or equal to the
minCount (in
our palettes such points have a 'transparent' color). For
-more details, check the internal code of vis_gene_p().
+more details, check the internal code of vis_gene_p().
Extract significant genes
@@ -1018,7 +1018,7 @@
SpatialExperiment support
SpatialExperiment class from SpatialExperiment.
-The functions vis_gene_p(), vis_gene(),
+The functions vis_gene_p(), vis_gene(),
vis_grid_clus(), vis_grid_gene(),
vis_clus(), vis_clus_p(),
geom_spatial() now work with SpatialExperiment
@@ -1108,7 +1108,7 @@ Generating our data (legacy)vis_clus_p() and
-
vis_gene_p(). Having the data from all images in a single
+vis_gene_p(). Having the data from all images in a single
object allows you to use the spot-level data from all images to compute
clusters and do other similar analyses to the ones you would do with
sc/snRNA-seq data. The script creates the
@@ -1377,189 +1377,191 @@ Reproducibilitylibrary("knitr")
knit("spatialLIBD.Rmd", tangle = TRUE)
+#> [1] "2024-07-16 17:05:18 EDT"#> [1] "2024-07-17 13:56:02 UTC"
+#> Time difference of 22.031 secs#> Time difference of 34.974 secsR session information.
@@ -1594,8 +1596,8 @@ #> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#> setting value
-#> version R version 4.4.0 (2024-04-24)
-#> os macOS Sonoma 14.5
-#> system aarch64, darwin20
+#> version R version 4.4.1 (2024-06-14)
+#> os Ubuntu 22.04.4 LTS
+#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
-#> tz America/New_York
-#> date 2024-07-16
-#> pandoc 3.2 @ /opt/homebrew/bin/ (via rmarkdown)
+#> tz UTC
+#> date 2024-07-17
+#> pandoc 3.2 @ /usr/bin/ (via rmarkdown)
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#>
-#> [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
+#> [1] /__w/_temp/Library
+#> [2] /usr/local/lib/R/site-library
+#> [3] /usr/local/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────Bibliography[4]
W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application
-Framework for R. R package version 1.8.1.1. 2024. URL:
-https://CRAN.R-project.org/package=shiny.
+Framework for R. R package version 1.8.1.1, https://github.com/rstudio/shiny. 2024. URL:
+https://shiny.posit.co/.
[5]
@@ -1616,7 +1618,7 @@ Bibliography[7]
C. Fay, V. Guyader, S. Rochette, et al. golem: A Framework for
Robust Shiny Applications. R package version 0.4.1. 2023. URL:
-https://CRAN.R-project.org/package=golem.
+https://github.com/ThinkR-open/golem.
[8]
@@ -1630,7 +1632,7 @@ Bibliography[9]
C. Gillespie. benchmarkme: Crowd Sourced System Benchmarks. R
package version 1.0.8. 2022. URL:
-https://CRAN.R-project.org/package=benchmarkme.
+https://github.com/csgillespie/benchmarkme.
[10]
@@ -1718,42 +1720,53 @@ Bibliography[20]
M. Morgan, V. Obenchain, J. Hester, et al. SummarizedExperiment:
SummarizedExperiment container. R package version 1.34.0. 2024.
+DOI:
+10.18129/B9.bioc.SummarizedExperiment.
URL:
https://bioconductor.org/packages/SummarizedExperiment.
[21] M. Morgan and L. Shepherd. AnnotationHub: Client to access -AnnotationHub resources. R package version 3.12.0. 2024. +AnnotationHub resources. R package version 3.12.0. 2024. DOI: +10.18129/B9.bioc.AnnotationHub. +URL: +https://bioconductor.org/packages/AnnotationHub.
[22] M. Morgan and L. Shepherd. ExperimentHub: Client to access -ExperimentHub resources. R package version 2.12.0. 2024. +ExperimentHub resources. R package version 2.12.0. 2024. DOI: +10.18129/B9.bioc.ExperimentHub. +URL: +https://bioconductor.org/packages/ExperimentHub.
[23] E. Neuwirth. RColorBrewer: ColorBrewer Palettes. R package -version 1.1-3. 2022. URL: -https://CRAN.R-project.org/package=RColorBrewer. +version 1.1-3. 2022.
[24] A. Oleś. BiocStyle: Standard styles for vignettes and other -Bioconductor documents. R package version 2.32.1. 2024. URL: -https://github.com/Bioconductor/BiocStyle. +Bioconductor documents. R package version 2.32.1. 2024. DOI: +10.18129/B9.bioc.BiocStyle. +URL: +https://bioconductor.org/packages/BiocStyle.
[25] J. Ooms. magick: Advanced Graphics and Image-Processing in R. R -package version 2.8.3. 2024. URL: -https://CRAN.R-project.org/package=magick. +package version 2.8.4. 2024. URL: +https://docs.ropensci.org/magick/https://ropensci.r-universe.dev/magick.
[26] H. Pagès, M. Lawrence, and P. Aboyoun. S4Vectors: Foundation of vector-like and list-like containers in Bioconductor. R package -version 0.42.1. 2024. URL: +version 0.42.1. 2024. DOI: +10.18129/B9.bioc.S4Vectors. +URL: https://bioconductor.org/packages/S4Vectors.
@@ -1789,7 +1802,10 @@
Bibliography[31] L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across -Sessions. R package version 2.12.0. 2024. +Sessions. R package version 2.12.0. 2024. DOI: +10.18129/B9.bioc.BiocFileCache. +URL: +https://bioconductor.org/packages/BiocFileCache.
[32]
@@ -1812,14 +1828,14 @@ Bibliography[35]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. R package version 1.2.2. 2021. URL:
-https://CRAN.R-project.org/package=sessioninfo.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
[36] C. Wilke. cowplot: Streamlined Plot Theme and Plot Annotations for ‘ggplot2’. R package version 1.1.3. 2024. URL: -https://CRAN.R-project.org/package=cowplot. +https://wilkelab.org/cowplot/.
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@@ -1832,7 +1848,7 @@ Bibliography[38]
Y. Xie, J. Cheng, and X. Tan. DT: A Wrapper of the JavaScript
Library ‘DataTables’. R package version 0.33. 2024. URL:
-https://CRAN.R-project.org/package=DT.
+https://github.com/rstudio/DT.
Authors and Citation
spatialLIBD
-
run_app() now offers the option to chose any of the paletteer::paletteer_d color palettes for discrete variables.
-
-
Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
+Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
-
run_app() now looks for columns that end with ’_colors’ in their name which can be used to pre-specify colors for any companion variables. For example if you have spe$my_groups and spe$my_groups_colors then the second one can specify the colors that will be used for visualizing spe$my_groups. This makes specifying default colors more flexible than before, and the user is still free to change them if necessary.
run_app() now offers the option to chose any of the paletteer::paletteer_d color palettes for discrete variables.Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.Polychrome has been replaced as a dependency by paletteer. Note that Polychrome::palette36 is still the default.
run_app() now looks for columns that end with ’_colors’ in their name which can be used to pre-specify colors for any companion variables. For example if you have spe$my_groups and spe$my_groups_colors then the second one can specify the colors that will be used for visualizing spe$my_groups. This makes specifying default colors more flexible than before, and the user is still free to change them if necessary.spatialLIBD 1
spatialLIBD 1.7.6
NEW FEATURES
-
-
vis_gene_p(),vis_clus_p()and all related functions now have an argumentpoint_sizewhich lets you control how big the points are plotted. This can be useful for visualization purposes.
+ - The shiny app now has an input controlling the point size. If you increase it to say
5, then if you zoom in theclusters (interactive)panel, you can see larger spots when zooming in. - These features are related to https://github.com/LieberInstitute/spatialLIBD/issues/28 although the spot diameter is still not the true spot diameter. However, now you have more flexibility for visualizing the spots.
vis_gene_p(), vis_clus_p() and all related functions now have an argument point_size which lets you control how big the points are plotted. This can be useful for visualization purposes.
spatialLIBD
spatialLIBD 1.3.3
NEW FEATURES
-- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
+- Overall the package has been updated to use
SpatialExperiment version 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such as sce_image_gene_p() now has a shorter name vis_gene_p(). This update also changes these visualization functions to ONLY support SpatialExperiment objects instead of the original modified SingleCellExperiment objects.
- Updated citation information to reflect that https://doi.org/10.1038/s41593-020-00787-0 is now public. Also added a link on the README to https://doi.org/10.6084/m9.figshare.13623902.v1 for the manuscript high resolution images.
diff --git a/pkgdown.yml b/pkgdown.yml
index 46fd2df0..f01eec79 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,4 +6,4 @@ articles:
multi_gene_plots: multi_gene_plots.html
spatialLIBD: spatialLIBD.html
TenX_data_download: TenX_data_download.html
-last_built: 2024-07-16T21:00Z
+last_built: 2024-07-17T13:48Z
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diff --git a/reference/add10xVisiumAnalysis.html b/reference/add10xVisiumAnalysis.html
index da55e67a..6dd8b9b8 100644
--- a/reference/add10xVisiumAnalysis.html
+++ b/reference/add10xVisiumAnalysis.html
@@ -65,7 +65,7 @@
Add analysis data from a 10x Genomics Visium experiment to a SPE object
- Source: R/add10xVisiumAnalysis.R
+ Source: R/add10xVisiumAnalysis.R
add10xVisiumAnalysis.Rd
@@ -120,7 +120,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/add_images.html b/reference/add_images.html
index 37749b90..db2faadf 100644
--- a/reference/add_images.html
+++ b/reference/add_images.html
@@ -71,7 +71,7 @@
Add non-standard images with the same dimensions as current ones
- Source: R/add_images.R
+ Source: R/add_images.R
add_images.Rd
@@ -165,30 +165,29 @@ Examples
image_paths = c("151507" = "https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151507_tissue_lowres_image.png")
))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:18.72371 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
-#> 2024-07-16 17:00:29.794628 adding image for sample 151507
-#> 2024-07-16 17:00:30.766353 adding image for sample 151508
+#> 2024-07-17 13:48:26.600477 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:41.90188 adding image for sample 151507
+#> 2024-07-17 13:48:42.538745 adding image for sample 151508
#> Warning: No image was found for sample: 151508
-#> 2024-07-16 17:00:30.766579 adding image for sample 151509
+#> 2024-07-17 13:48:42.539054 adding image for sample 151509
#> Warning: No image was found for sample: 151509
-#> 2024-07-16 17:00:30.766725 adding image for sample 151510
+#> 2024-07-17 13:48:42.539261 adding image for sample 151510
#> Warning: No image was found for sample: 151510
-#> 2024-07-16 17:00:30.766858 adding image for sample 151669
+#> 2024-07-17 13:48:42.539459 adding image for sample 151669
#> Warning: No image was found for sample: 151669
-#> 2024-07-16 17:00:30.76698 adding image for sample 151670
+#> 2024-07-17 13:48:42.539652 adding image for sample 151670
#> Warning: No image was found for sample: 151670
-#> 2024-07-16 17:00:30.767101 adding image for sample 151671
+#> 2024-07-17 13:48:42.539843 adding image for sample 151671
#> Warning: No image was found for sample: 151671
-#> 2024-07-16 17:00:30.767222 adding image for sample 151672
+#> 2024-07-17 13:48:42.540033 adding image for sample 151672
#> Warning: No image was found for sample: 151672
-#> 2024-07-16 17:00:30.76734 adding image for sample 151673
+#> 2024-07-17 13:48:42.540223 adding image for sample 151673
#> Warning: No image was found for sample: 151673
-#> 2024-07-16 17:00:30.767458 adding image for sample 151674
+#> 2024-07-17 13:48:42.540414 adding image for sample 151674
#> Warning: No image was found for sample: 151674
-#> 2024-07-16 17:00:30.767576 adding image for sample 151675
+#> 2024-07-17 13:48:42.540604 adding image for sample 151675
#> Warning: No image was found for sample: 151675
-#> 2024-07-16 17:00:30.767696 adding image for sample 151676
+#> 2024-07-17 13:48:42.540791 adding image for sample 151676
#> Warning: No image was found for sample: 151676
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
diff --git a/reference/add_key.html b/reference/add_key.html
index 7dce6d11..220b5ded 100644
--- a/reference/add_key.html
+++ b/reference/add_key.html
@@ -65,7 +65,7 @@
@@ -124,8 +124,7 @@ Examples
spe$key_original <- NULL
head(spe$key)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:33.017537 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:48:44.910936 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> [1] "151507_AAACAACGAATAGTTC-1" "151507_AAACAAGTATCTCCCA-1"
#> [3] "151507_AAACAATCTACTAGCA-1" "151507_AAACACCAATAACTGC-1"
#> [5] "151507_AAACAGCTTTCAGAAG-1" "151507_AAACAGGGTCTATATT-1"
diff --git a/reference/add_qc_metrics-1.png b/reference/add_qc_metrics-1.png
index cade42d4..2e65d510 100644
Binary files a/reference/add_qc_metrics-1.png and b/reference/add_qc_metrics-1.png differ
diff --git a/reference/add_qc_metrics-2.png b/reference/add_qc_metrics-2.png
index 837a248e..d0142804 100644
Binary files a/reference/add_qc_metrics-2.png and b/reference/add_qc_metrics-2.png differ
diff --git a/reference/add_qc_metrics-3.png b/reference/add_qc_metrics-3.png
index 479ba97d..2b8c7ead 100644
Binary files a/reference/add_qc_metrics-3.png and b/reference/add_qc_metrics-3.png differ
diff --git a/reference/add_qc_metrics-4.png b/reference/add_qc_metrics-4.png
index cd287d06..39a4439a 100644
Binary files a/reference/add_qc_metrics-4.png and b/reference/add_qc_metrics-4.png differ
diff --git a/reference/add_qc_metrics-5.png b/reference/add_qc_metrics-5.png
index e6624e22..e1b6345a 100644
Binary files a/reference/add_qc_metrics-5.png and b/reference/add_qc_metrics-5.png differ
diff --git a/reference/add_qc_metrics-6.png b/reference/add_qc_metrics-6.png
index 95168130..70357959 100644
Binary files a/reference/add_qc_metrics-6.png and b/reference/add_qc_metrics-6.png differ
diff --git a/reference/add_qc_metrics-7.png b/reference/add_qc_metrics-7.png
index b21b0b71..0a06596e 100644
Binary files a/reference/add_qc_metrics-7.png and b/reference/add_qc_metrics-7.png differ
diff --git a/reference/add_qc_metrics-8.png b/reference/add_qc_metrics-8.png
index 41ab0f4e..24a2c0e0 100644
Binary files a/reference/add_qc_metrics-8.png and b/reference/add_qc_metrics-8.png differ
diff --git a/reference/add_qc_metrics.html b/reference/add_qc_metrics.html
index db6a4d92..9c72a786 100644
--- a/reference/add_qc_metrics.html
+++ b/reference/add_qc_metrics.html
@@ -67,7 +67,7 @@
Quality Control for Spatial Data
- Source: R/add_qc_metrics.R
+ Source: R/add_qc_metrics.R
add_qc_metrics.Rd
@@ -144,8 +144,7 @@ Author
Examples
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:43.634355 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f563a40ecf7_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
+#> 2024-07-17 13:49:00.582195 loading file /github/home/.cache/R/BiocFileCache/49872dc0d45_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
diff --git a/reference/annotate_registered_clusters.html b/reference/annotate_registered_clusters.html
index fd6421d6..50b43af5 100644
--- a/reference/annotate_registered_clusters.html
+++ b/reference/annotate_registered_clusters.html
@@ -67,7 +67,7 @@
Annotated spatially-registered clusters
- Source: R/annotate_registered_clusters.R
+ Source: R/annotate_registered_clusters.R
annotate_registered_clusters.Rd
@@ -137,8 +137,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:51.762523 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:13.326528 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/check_modeling_results.html b/reference/check_modeling_results.html
index e56f7419..f95254df 100644
--- a/reference/check_modeling_results.html
+++ b/reference/check_modeling_results.html
@@ -64,7 +64,7 @@
Check input modeling_results
- Source: R/check_modeling_results.R
+ Source: R/check_modeling_results.R
check_modeling_results.Rd
@@ -108,8 +108,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:52.678188 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:14.441658 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Check the object
xx <- check_modeling_results(modeling_results)
diff --git a/reference/check_sce.html b/reference/check_sce.html
index 8a937cdf..fdc02746 100644
--- a/reference/check_sce.html
+++ b/reference/check_sce.html
@@ -66,7 +66,7 @@
@@ -131,8 +131,7 @@ Examples
## Check the object
check_sce(sce_example)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:53.63802 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:15.651297 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
#> class: SingleCellExperiment
#> dim: 33538 47681
#> metadata(1): image
diff --git a/reference/check_sce_layer.html b/reference/check_sce_layer.html
index e6129283..c926c5cf 100644
--- a/reference/check_sce_layer.html
+++ b/reference/check_sce_layer.html
@@ -64,7 +64,7 @@
Check input sce_layer
- Source: R/check_sce_layer.R
+ Source: R/check_sce_layer.R
check_sce_layer.Rd
@@ -112,8 +112,7 @@ Examples
## Obtain example data from the HumanPilot project
## (Maynard, Collado-Torres, et al, 2021)
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:55.536908 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:18.090538 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Check the pseudo-bulked data
check_sce_layer(sce_layer)
diff --git a/reference/check_spe.html b/reference/check_spe.html
index 00f18aab..262e37d5 100644
--- a/reference/check_spe.html
+++ b/reference/check_spe.html
@@ -64,7 +64,7 @@
@@ -123,8 +123,7 @@ Examples
## Check the object
check_spe(spe)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:56.493054 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:19.444343 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> class: SpatialExperiment
#> dim: 33538 47681
#> metadata(0):
diff --git a/reference/cluster_export.html b/reference/cluster_export.html
index 576e5969..41dcf6be 100644
--- a/reference/cluster_export.html
+++ b/reference/cluster_export.html
@@ -67,7 +67,7 @@
Export a column with cluster results
- Source: R/cluster_export.R
+ Source: R/cluster_export.R
cluster_export.Rd
@@ -134,8 +134,7 @@ Examples
cluster_export(spe, "spatialLIBD")
cluster_export(spe, "GraphBased")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:06.836252 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:34.076008 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
diff --git a/reference/cluster_import.html b/reference/cluster_import.html
index feed9a97..585bc91f 100644
--- a/reference/cluster_import.html
+++ b/reference/cluster_import.html
@@ -66,7 +66,7 @@
@@ -137,12 +137,11 @@ Examples
## Re-import them
colData(cluster_import(spe))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:17.501482 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:49.230922 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/spatialLIBD' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/spatialLIBD' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/GraphBased' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/GraphBased' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> DataFrame with 47681 rows and 71 columns
#> key sample_id Cluster sum_umi
diff --git a/reference/enough_ram.html b/reference/enough_ram.html
index 1aefe5c0..17fada89 100644
--- a/reference/enough_ram.html
+++ b/reference/enough_ram.html
@@ -63,7 +63,7 @@
Determine if you have enough RAM memory
- Source: R/enough_ram.R
+ Source: R/enough_ram.R
enough_ram.Rd
diff --git a/reference/fetch_data.html b/reference/fetch_data.html
index 860fcc8a..626b28ea 100644
--- a/reference/fetch_data.html
+++ b/reference/fetch_data.html
@@ -71,7 +71,7 @@
Download the Human DLPFC Visium data from LIBD
- Source: R/fetch_data.R
+ Source: R/fetch_data.R
fetch_data.Rd
@@ -166,8 +166,7 @@ Examples
## Download the SingleCellExperiment object
## at the layer-level
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:28.986594 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:04.599487 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Explore the data
sce_layer
diff --git a/reference/frame_limits.html b/reference/frame_limits.html
index 0a945d2b..ce67964f 100644
--- a/reference/frame_limits.html
+++ b/reference/frame_limits.html
@@ -73,7 +73,7 @@
@@ -154,8 +154,7 @@ Examples
## Obtain the frame limits for one sample
frame_limits(spe, sampleid = "151673")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:30.408348 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:07.106212 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> $y_min
#> [1] 64
#>
diff --git a/reference/gene_set_enrichment.html b/reference/gene_set_enrichment.html
index 58358fa3..69f114cc 100644
--- a/reference/gene_set_enrichment.html
+++ b/reference/gene_set_enrichment.html
@@ -68,7 +68,7 @@
Evaluate the enrichment for a list of gene sets
- Source: R/gene_set_enrichment.R
+ Source: R/gene_set_enrichment.R
gene_set_enrichment.Rd
@@ -176,8 +176,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:40.855511 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:21.075222 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/gene_set_enrichment_plot-1.png b/reference/gene_set_enrichment_plot-1.png
index d68b19ec..d366f433 100644
Binary files a/reference/gene_set_enrichment_plot-1.png and b/reference/gene_set_enrichment_plot-1.png differ
diff --git a/reference/gene_set_enrichment_plot-2.png b/reference/gene_set_enrichment_plot-2.png
index 78df31f0..dbc691ef 100644
Binary files a/reference/gene_set_enrichment_plot-2.png and b/reference/gene_set_enrichment_plot-2.png differ
diff --git a/reference/gene_set_enrichment_plot.html b/reference/gene_set_enrichment_plot.html
index 40392d13..ffdc11f2 100644
--- a/reference/gene_set_enrichment_plot.html
+++ b/reference/gene_set_enrichment_plot.html
@@ -64,7 +64,7 @@
Plot the gene set enrichment results
- Source: R/gene_set_enrichment_plot.R
+ Source: R/gene_set_enrichment_plot.R
gene_set_enrichment_plot.Rd
@@ -178,8 +178,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:41.867526 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:22.531835 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/geom_spatial-1.png b/reference/geom_spatial-1.png
index 64fd3d7a..946c446a 100644
Binary files a/reference/geom_spatial-1.png and b/reference/geom_spatial-1.png differ
diff --git a/reference/geom_spatial.html b/reference/geom_spatial.html
index 5d50b49e..42e5c07c 100644
--- a/reference/geom_spatial.html
+++ b/reference/geom_spatial.html
@@ -66,7 +66,7 @@
A ggplot2 layer for visualizing the Visium histology
- Source: R/geom_spatial.R
+ Source: R/geom_spatial.R
geom_spatial.Rd
@@ -74,7 +74,7 @@ A ggplot2 layer for visualizing the Visium histology
This function defines a ggplot2::layer() for visualizing the histology
image from Visium. It can be combined with other ggplot2 functions for
visualizing the clusters as in vis_clus_p() or gene-level information
-as in vis_gene_p().
+as in vis_gene_p().
@@ -175,8 +175,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:43.207432 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:24.396394 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/get_colors.html b/reference/get_colors.html
index e49a44bf..dfbeb5c2 100644
--- a/reference/get_colors.html
+++ b/reference/get_colors.html
@@ -64,7 +64,7 @@
Obtain the colors for a set of cluster names
- Source: R/get_colors.R
+ Source: R/get_colors.R
get_colors.Rd
@@ -84,7 +84,7 @@ Arguments
- colors
A vector of colors. If NULL then a set of default colors will
be used when clusters has less than 12 unique values, otherwise
-Polychrome::palette36 will be used which can
+Polychrome::palette36 will be used which can
generate up to 36 unique colors. If the number of unique clusters is beyond
36 then this function will fail.
Examples
## Obtain the necessary data
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:54.433623 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:39.853193 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Example layer colors with the corresponding names
get_colors(libd_layer_colors, sce_layer$layer_guess)
diff --git a/reference/img_edit-1.png b/reference/img_edit-1.png
index 94154fc3..9af3f312 100644
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diff --git a/reference/img_edit.html b/reference/img_edit.html
index 9df344ec..004b6d82 100644
--- a/reference/img_edit.html
+++ b/reference/img_edit.html
@@ -65,7 +65,7 @@
@@ -222,8 +222,7 @@ Examples
x <- img_edit(spe, sampleid = "151507", brightness = 25)
plot(x)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:56.683064 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:41.084926 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/img_update.html b/reference/img_update.html
index 5b6a0f39..5d92fe1f 100644
--- a/reference/img_update.html
+++ b/reference/img_update.html
@@ -63,7 +63,7 @@
@@ -139,8 +139,7 @@ Examples
## Reduce brightness to 25% and update the imgData()
imgData(img_update(spe, sampleid = "151507", brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:07.614049 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:56.77859 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/img_update_all.html b/reference/img_update_all.html
index e322e40f..8a0c7996 100644
--- a/reference/img_update_all.html
+++ b/reference/img_update_all.html
@@ -65,7 +65,7 @@
Update the images for all samples
- Source: R/img_update_all.R
+ Source: R/img_update_all.R
img_update_all.Rd
@@ -138,8 +138,7 @@ Examples
## update the imgData()
imgData(img_update_all(spe, brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:17.633699 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:11.011904 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 24 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/index.html b/reference/index.html
index 3d629a4c..fdcce2ae 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -249,6 +249,10 @@ All functions vis_gene()
Sample spatial gene visualization
+
+
+ Sample spatial gene visualization workhorse function
diff --git a/reference/layer_boxplot-1.png b/reference/layer_boxplot-1.png
index d27f4b41..d6cfd681 100644
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index a10d0a22..96e6f0bb 100644
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diff --git a/reference/layer_boxplot-5.png b/reference/layer_boxplot-5.png
index 14ac9b54..c8eb3bae 100644
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diff --git a/reference/layer_boxplot-6.png b/reference/layer_boxplot-6.png
index f44309f3..5dea49a5 100644
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diff --git a/reference/layer_boxplot-7.png b/reference/layer_boxplot-7.png
index f6564386..a247b555 100644
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diff --git a/reference/layer_boxplot.html b/reference/layer_boxplot.html
index 90de61cd..302acf11 100644
--- a/reference/layer_boxplot.html
+++ b/reference/layer_boxplot.html
@@ -65,7 +65,7 @@
Layer-level (group-level) boxplots
- Source: R/layer_boxplot.R
+ Source: R/layer_boxplot.R
layer_boxplot.Rd
@@ -185,11 +185,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:28.442408 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:28.503014 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:29.096088 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:29.384093 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Top 2 genes from the enrichment model
sig_genes <- sig_genes_extract_all(
diff --git a/reference/layer_matrix_plot-1.png b/reference/layer_matrix_plot-1.png
index d9460395..4f269d7a 100644
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diff --git a/reference/layer_matrix_plot-2.png b/reference/layer_matrix_plot-2.png
index 8e3e7d6d..2f29029a 100644
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diff --git a/reference/layer_matrix_plot.html b/reference/layer_matrix_plot.html
index d2728bb4..d5cd6750 100644
--- a/reference/layer_matrix_plot.html
+++ b/reference/layer_matrix_plot.html
@@ -66,7 +66,7 @@
Visualize a matrix of values across human brain layers
- Source: R/layer_matrix_plot.R
+ Source: R/layer_matrix_plot.R
layer_matrix_plot.Rd
diff --git a/reference/layer_stat_cor.html b/reference/layer_stat_cor.html
index be43eee0..208b193a 100644
--- a/reference/layer_stat_cor.html
+++ b/reference/layer_stat_cor.html
@@ -63,7 +63,7 @@
Layer modeling correlation of statistics
- Source: R/layer_stat_cor.R
+ Source: R/layer_stat_cor.R
layer_stat_cor.Rd
@@ -156,8 +156,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:31.53213 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:32.756558 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/layer_stat_cor_plot-1.png b/reference/layer_stat_cor_plot-1.png
index 5019ec42..72baf49d 100644
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index bdb90ead..d7368ed7 100644
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diff --git a/reference/layer_stat_cor_plot-3.png b/reference/layer_stat_cor_plot-3.png
index c9a9bcf0..4b97784a 100644
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diff --git a/reference/layer_stat_cor_plot-4.png b/reference/layer_stat_cor_plot-4.png
index ee32ca9a..d74ca04c 100644
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diff --git a/reference/layer_stat_cor_plot-5.png b/reference/layer_stat_cor_plot-5.png
index 2e2b880f..a6ca399d 100644
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diff --git a/reference/layer_stat_cor_plot.html b/reference/layer_stat_cor_plot.html
index d08a54a2..7670f03a 100644
--- a/reference/layer_stat_cor_plot.html
+++ b/reference/layer_stat_cor_plot.html
@@ -66,7 +66,7 @@
Visualize the layer modeling correlation of statistics
- Source: R/layer_stat_cor_plot.R
+ Source: R/layer_stat_cor_plot.R
layer_stat_cor_plot.Rd
@@ -145,8 +145,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:32.436771 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:33.883339 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/libd_layer_colors.html b/reference/libd_layer_colors.html
index d2df282e..6a843fec 100644
--- a/reference/libd_layer_colors.html
+++ b/reference/libd_layer_colors.html
@@ -64,7 +64,7 @@
diff --git a/reference/locate_images.html b/reference/locate_images.html
index 62727198..8cbe293c 100644
--- a/reference/locate_images.html
+++ b/reference/locate_images.html
@@ -65,7 +65,7 @@
diff --git a/reference/multi_gene_pca.html b/reference/multi_gene_pca.html
index 58575a98..334fbe7d 100644
--- a/reference/multi_gene_pca.html
+++ b/reference/multi_gene_pca.html
@@ -68,7 +68,7 @@
Combine multiple continuous variables through PCA
- Source: R/multi_gene_pca.R
+ Source: R/multi_gene_pca.R
multi_gene_pca.Rd
diff --git a/reference/multi_gene_sparsity.html b/reference/multi_gene_sparsity.html
index 042ec2af..2ababa43 100644
--- a/reference/multi_gene_sparsity.html
+++ b/reference/multi_gene_sparsity.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by proportion of positive values
- Source: R/multi_gene_sparsity.R
+ Source: R/multi_gene_sparsity.R
multi_gene_sparsity.Rd
diff --git a/reference/multi_gene_z_score.html b/reference/multi_gene_z_score.html
index 612273f5..ce8a878a 100644
--- a/reference/multi_gene_z_score.html
+++ b/reference/multi_gene_z_score.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by averaging Z scores
- Source: R/multi_gene_z_score.R
+ Source: R/multi_gene_z_score.R
multi_gene_z_score.Rd
diff --git a/reference/prep_stitched_data.html b/reference/prep_stitched_data.html
index 0c4a592e..36678e3a 100644
--- a/reference/prep_stitched_data.html
+++ b/reference/prep_stitched_data.html
@@ -68,7 +68,7 @@
Prepare stitched data for plotting
- Source: R/prep_stitched_data.R
+ Source: R/prep_stitched_data.R
prep_stitched_data.Rd
diff --git a/reference/read10xVisiumAnalysis.html b/reference/read10xVisiumAnalysis.html
index b36ef451..7e04bd5b 100644
--- a/reference/read10xVisiumAnalysis.html
+++ b/reference/read10xVisiumAnalysis.html
@@ -64,7 +64,7 @@
Load analysis data from a 10x Genomics Visium experiment
- Source: R/read10xVisiumAnalysis.R
+ Source: R/read10xVisiumAnalysis.R
read10xVisiumAnalysis.Rd
@@ -118,7 +118,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/read10xVisiumWrapper.html b/reference/read10xVisiumWrapper.html
index 56b267a0..c8d01991 100644
--- a/reference/read10xVisiumWrapper.html
+++ b/reference/read10xVisiumWrapper.html
@@ -66,7 +66,7 @@
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
- Source: R/read10xVisiumWrapper.R
+ Source: R/read10xVisiumWrapper.R
read10xVisiumWrapper.Rd
@@ -162,7 +162,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/registration_block_cor.html b/reference/registration_block_cor.html
index 33000024..126fabd2 100644
--- a/reference/registration_block_cor.html
+++ b/reference/registration_block_cor.html
@@ -66,7 +66,7 @@
Spatial registration: block correlation
- Source: R/registration_block_cor.R
+ Source: R/registration_block_cor.R
registration_block_cor.Rd
@@ -121,36 +121,36 @@ See also
Examples
example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:34.847415 make pseudobulk object
-#> 2024-07-16 17:02:34.953364 drop lowly expressed genes
-#> 2024-07-16 17:02:34.99097 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:37.088175 make pseudobulk object
+#> 2024-07-17 13:51:37.267087 drop lowly expressed genes
+#> 2024-07-17 13:51:37.336566 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -179,10 +179,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:35.032307 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:37.415555 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -198,8 +198,8 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:35.038484 run duplicateCorrelation()
-#> 2024-07-16 17:02:35.564971 The estimated correlation is: -0.0187869166526901
+#> 2024-07-17 13:51:37.428263 run duplicateCorrelation()
+#> 2024-07-17 13:51:38.691552 The estimated correlation is: -0.0187869166526901
diff --git a/reference/registration_model.html b/reference/registration_model.html
index 7a26252f..c96dc0da 100644
--- a/reference/registration_model.html
+++ b/reference/registration_model.html
@@ -67,7 +67,7 @@
Spatial registration: model
- Source: R/registration_model.R
+ Source: R/registration_model.R
registration_model.Rd
@@ -125,34 +125,34 @@ See also
Examples
example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:35.873124 make pseudobulk object
-#> 2024-07-16 17:02:35.960837 drop lowly expressed genes
-#> 2024-07-16 17:02:35.986325 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:39.129951 make pseudobulk object
+#> 2024-07-17 13:51:39.31554 drop lowly expressed genes
+#> 2024-07-17 13:51:39.370617 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -181,7 +181,7 @@ Examples
#> D_S S D 14
#> E_S S E 11
registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:36.024617 create model matrix
+#> 2024-07-17 13:51:39.447064 create model matrix
head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
diff --git a/reference/registration_pseudobulk.html b/reference/registration_pseudobulk.html
index 653d03b2..8722ef39 100644
--- a/reference/registration_pseudobulk.html
+++ b/reference/registration_pseudobulk.html
@@ -64,7 +64,7 @@
Spatial registration: pseudobulk
- Source: R/registration_pseudobulk.R
+ Source: R/registration_pseudobulk.R
registration_pseudobulk.Rd
@@ -159,9 +159,9 @@ Examples
## Pseudo-bulk
sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.341187 make pseudobulk object
-#> 2024-07-16 17:02:36.4321 drop lowly expressed genes
-#> 2024-07-16 17:02:36.458483 normalize expression
+#> 2024-07-17 13:51:39.903902 make pseudobulk object
+#> 2024-07-17 13:51:40.056716 drop lowly expressed genes
+#> 2024-07-17 13:51:40.111023 normalize expression
colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
diff --git a/reference/registration_stats_anova.html b/reference/registration_stats_anova.html
index 1cf15645..cdc9d765 100644
--- a/reference/registration_stats_anova.html
+++ b/reference/registration_stats_anova.html
@@ -66,7 +66,7 @@
Spatial registration: compute ANOVA statistics
- Source: R/registration_stats_anova.R
+ Source: R/registration_stats_anova.R
registration_stats_anova.Rd
@@ -153,38 +153,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.908 make pseudobulk object
-#> 2024-07-16 17:02:36.981269 drop lowly expressed genes
-#> 2024-07-16 17:02:37.007143 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:40.701746 make pseudobulk object
+#> 2024-07-17 13:51:40.884268 drop lowly expressed genes
+#> 2024-07-17 13:51:40.939518 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -213,10 +213,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:37.061168 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:41.012467 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -232,14 +232,14 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:37.066375 run duplicateCorrelation()
-#> 2024-07-16 17:02:37.583667 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:41.024125 run duplicateCorrelation()
+#> 2024-07-17 13:51:42.289985 The estimated correlation is: -0.0187869166526901
results_anova <- registration_stats_anova(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.589856 computing F-statistics
+#> 2024-07-17 13:51:42.302664 computing F-statistics
head(results_anova)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1328075 0.93918553 0.9951876 5.499488 ENSG1 gene1
@@ -254,7 +254,7 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.615244 computing F-statistics
+#> 2024-07-17 13:51:42.365534 computing F-statistics
head(results_anova_nan)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1357180 0.93736053 0.9943765 5.499488 ENSG1 gene1
@@ -276,7 +276,7 @@ Examples
covars = NULL,
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "nocovar"
)
-#> 2024-07-16 17:02:37.632809 computing F-statistics
+#> 2024-07-17 13:51:42.415614 computing F-statistics
head(results_anova_nocovar)
#> f_stat_nocovar p_value_nocovar fdr_nocovar AveExpr_nocovar ensembl gene
#> 1 0.1393641 0.9351345 0.9962097 5.499488 ENSG1 gene1
diff --git a/reference/registration_stats_enrichment.html b/reference/registration_stats_enrichment.html
index c2fc717e..b97c7f9c 100644
--- a/reference/registration_stats_enrichment.html
+++ b/reference/registration_stats_enrichment.html
@@ -65,7 +65,7 @@
Spatial registration: compute enrichment statistics
- Source: R/registration_stats_enrichment.R
+ Source: R/registration_stats_enrichment.R
registration_stats_enrichment.Rd
@@ -144,38 +144,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:37.992936 make pseudobulk object
-#> 2024-07-16 17:02:38.06571 drop lowly expressed genes
-#> 2024-07-16 17:02:38.091375 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:42.992514 make pseudobulk object
+#> 2024-07-17 13:51:43.146693 drop lowly expressed genes
+#> 2024-07-17 13:51:43.201202 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -204,10 +204,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:38.129501 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:43.274381 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -223,15 +223,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:38.134799 run duplicateCorrelation()
-#> 2024-07-16 17:02:38.654908 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:43.285637 run duplicateCorrelation()
+#> 2024-07-17 13:51:44.583617 The estimated correlation is: -0.0187869166526901
results_enrichment <- registration_stats_enrichment(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.657236 computing enrichment statistics
-#> 2024-07-16 17:02:38.701689 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.587859 computing enrichment statistics
+#> 2024-07-17 13:51:44.705956 extract and reformat enrichment results
head(results_enrichment)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1482017 0.5610669 -0.3612235 -0.3458508 0.88374480 0.58130631
@@ -260,8 +260,8 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.712787 computing enrichment statistics
-#> 2024-07-16 17:02:38.771541 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.739083 computing enrichment statistics
+#> 2024-07-17 13:51:44.842281 extract and reformat enrichment results
head(results_enrichment_nan)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1497747 0.56711100 -0.3650801 -0.3495404 0.88252049 0.57727506
diff --git a/reference/registration_stats_pairwise.html b/reference/registration_stats_pairwise.html
index c11a5e44..03bff131 100644
--- a/reference/registration_stats_pairwise.html
+++ b/reference/registration_stats_pairwise.html
@@ -66,7 +66,7 @@
Spatial registration: compute pairwise statistics
- Source: R/registration_stats_pairwise.R
+ Source: R/registration_stats_pairwise.R
registration_stats_pairwise.Rd
@@ -146,38 +146,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:39.085978 make pseudobulk object
-#> 2024-07-16 17:02:39.159736 drop lowly expressed genes
-#> 2024-07-16 17:02:39.185678 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:45.303165 make pseudobulk object
+#> 2024-07-17 13:51:45.456984 drop lowly expressed genes
+#> 2024-07-17 13:51:45.511196 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -206,10 +206,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:39.224065 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:45.621594 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -225,15 +225,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:39.22931 run duplicateCorrelation()
-#> 2024-07-16 17:02:39.781072 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:45.632849 run duplicateCorrelation()
+#> 2024-07-17 13:51:46.88774 The estimated correlation is: -0.0187869166526901
results_pairwise <- registration_stats_pairwise(sce_pseudo,
registration_mod, block_cor,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.782515 running the baseline pairwise model
-#> 2024-07-16 17:02:39.790292 computing pairwise statistics
+#> 2024-07-17 13:51:46.889688 running the baseline pairwise model
+#> 2024-07-17 13:51:46.906431 computing pairwise statistics
head(results_pairwise)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2393683 0.29771391 0.28880637 0.5370822 0.5281747
@@ -277,8 +277,8 @@ Examples
block_cor = NaN,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.811874 running the baseline pairwise model
-#> 2024-07-16 17:02:39.818697 computing pairwise statistics
+#> 2024-07-17 13:51:46.971696 running the baseline pairwise model
+#> 2024-07-17 13:51:46.989106 computing pairwise statistics
head(results_pairwise_nan)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2419770 0.30095840 0.29195379 0.5429354 0.5339308
diff --git a/reference/registration_wrapper.html b/reference/registration_wrapper.html
index 546b32eb..a04252d2 100644
--- a/reference/registration_wrapper.html
+++ b/reference/registration_wrapper.html
@@ -68,7 +68,7 @@
Spatial registration: wrapper function
- Source: R/registration_wrapper.R
+ Source: R/registration_wrapper.R
registration_wrapper.Rd
@@ -200,18 +200,18 @@ Examples
sce,
"Cell_Cycle", "sample_id", c("age"), "ensembl", "gene_name", "wrapper"
)
-#> 2024-07-16 17:02:40.149028 make pseudobulk object
-#> 2024-07-16 17:02:40.221379 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:02:40.231996 drop lowly expressed genes
-#> 2024-07-16 17:02:40.27465 normalize expression
-#> 2024-07-16 17:02:40.303232 create model matrix
-#> 2024-07-16 17:02:40.308019 run duplicateCorrelation()
-#> 2024-07-16 17:02:41.300298 The estimated correlation is: -0.0783081238514527
-#> 2024-07-16 17:02:41.301437 computing enrichment statistics
-#> 2024-07-16 17:02:41.342436 extract and reformat enrichment results
-#> 2024-07-16 17:02:41.35071 running the baseline pairwise model
-#> 2024-07-16 17:02:41.357315 computing pairwise statistics
-#> 2024-07-16 17:02:41.380689 computing F-statistics
+#> 2024-07-17 13:51:47.541862 make pseudobulk object
+#> 2024-07-17 13:51:47.707925 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:51:47.729853 drop lowly expressed genes
+#> 2024-07-17 13:51:47.785167 normalize expression
+#> 2024-07-17 13:51:47.8429 create model matrix
+#> 2024-07-17 13:51:47.853499 run duplicateCorrelation()
+#> 2024-07-17 13:51:50.267571 The estimated correlation is: -0.0783081238514532
+#> 2024-07-17 13:51:50.269845 computing enrichment statistics
+#> 2024-07-17 13:51:50.386595 extract and reformat enrichment results
+#> 2024-07-17 13:51:50.412505 running the baseline pairwise model
+#> 2024-07-17 13:51:50.430847 computing pairwise statistics
+#> 2024-07-17 13:51:50.505218 computing F-statistics
diff --git a/reference/run_app.html b/reference/run_app.html
index d23cb924..2cca4ddc 100644
--- a/reference/run_app.html
+++ b/reference/run_app.html
@@ -65,7 +65,7 @@
@@ -270,7 +270,7 @@ Examples
vars <- colnames(colData(spe))
## Set default cluster colors
- colors_BayesSpace <- Polychrome::palette36.colors(28)
+ colors_BayesSpace <- Polychrome::palette36.colors(28)
names(colors_BayesSpace) <- c(1:28)
m <- match(as.character(spe$BayesSpace_harmony_09), names(colors_BayesSpace))
stopifnot(all(!is.na(m)))
diff --git a/reference/sce_to_spe.html b/reference/sce_to_spe.html
index 84fd3093..e0797fb6 100644
--- a/reference/sce_to_spe.html
+++ b/reference/sce_to_spe.html
@@ -67,7 +67,7 @@
@@ -127,8 +127,7 @@ Examples
## Transform it to a SpatialExperiment object
spe <- sce_to_spe(sce)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:43.103369 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:52.727073 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/sig_genes_extract.html b/reference/sig_genes_extract.html
index 0ecdbcc3..4c448c85 100644
--- a/reference/sig_genes_extract.html
+++ b/reference/sig_genes_extract.html
@@ -67,7 +67,7 @@
Extract significant genes
- Source: R/sig_genes_extract.R
+ Source: R/sig_genes_extract.R
sig_genes_extract.Rd
@@ -156,11 +156,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:52.484674 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:05.714888 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:53.182388 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:06.659035 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## anova top 10 genes
sig_genes_extract(
diff --git a/reference/sig_genes_extract_all.html b/reference/sig_genes_extract_all.html
index 17516a57..4a42f61e 100644
--- a/reference/sig_genes_extract_all.html
+++ b/reference/sig_genes_extract_all.html
@@ -65,7 +65,7 @@
Extract significant genes for all modeling results
- Source: R/sig_genes_extract_all.R
+ Source: R/sig_genes_extract_all.R
sig_genes_extract_all.Rd
@@ -128,11 +128,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.422915 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:10.311903 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.970561 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:11.371345 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## top 10 genes for all models
sig_genes_extract_all(
diff --git a/reference/sort_clusters.html b/reference/sort_clusters.html
index 8dccd3d7..675c4397 100644
--- a/reference/sort_clusters.html
+++ b/reference/sort_clusters.html
@@ -65,7 +65,7 @@
diff --git a/reference/spatialLIBD-package.html b/reference/spatialLIBD-package.html
index 148e52f3..c22a18c2 100644
--- a/reference/spatialLIBD-package.html
+++ b/reference/spatialLIBD-package.html
@@ -64,7 +64,7 @@
spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
- Source: R/spatialLIBD-package.R
+ Source: R/spatialLIBD-package.R
spatialLIBD-package.Rd
diff --git a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
index e6a4ba86..4dbbeb2a 100644
--- a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
+++ b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
@@ -69,7 +69,7 @@
Cell cluster t-statistics from Tran et al
- Source: R/data.R
+ Source: R/data.R
tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.Rd
diff --git a/reference/vis_clus-1.png b/reference/vis_clus-1.png
index b62ae3bc..fff9298e 100644
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diff --git a/reference/vis_clus-2.png b/reference/vis_clus-2.png
index 59f18aa4..4962aaef 100644
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diff --git a/reference/vis_clus-3.png b/reference/vis_clus-3.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus-4.png b/reference/vis_clus-4.png
index 7a08ba8a..fd74eca4 100644
Binary files a/reference/vis_clus-4.png and b/reference/vis_clus-4.png differ
diff --git a/reference/vis_clus.html b/reference/vis_clus.html
index 4c441931..29b47fed 100644
--- a/reference/vis_clus.html
+++ b/reference/vis_clus.html
@@ -65,7 +65,7 @@
@@ -242,8 +242,7 @@ Examples
)
print(p4)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:57.892758 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:14.053539 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_clus_p-1.png b/reference/vis_clus_p-1.png
index ac93117a..3a3d3926 100644
Binary files a/reference/vis_clus_p-1.png and b/reference/vis_clus_p-1.png differ
diff --git a/reference/vis_clus_p.html b/reference/vis_clus_p.html
index 0106b4be..1e416396 100644
--- a/reference/vis_clus_p.html
+++ b/reference/vis_clus_p.html
@@ -66,7 +66,7 @@
Sample spatial cluster visualization workhorse function
- Source: R/vis_clus_p.R
+ Source: R/vis_clus_p.R
vis_clus_p.Rd
@@ -74,7 +74,7 @@ Sample spatial cluster visualization workhorse function
This function visualizes the clusters for one given sample at the spot-level
using (by default) the histology information on the background. This is the
function that does all the plotting behind vis_clus(). To visualize
-gene-level (or any continuous variable) use vis_gene_p().
+gene-level (or any continuous variable) use vis_gene_p().
@@ -202,8 +202,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:52:33.265544 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene-1.png b/reference/vis_gene-1.png
index dd3f3f08..3585ea9b 100644
Binary files a/reference/vis_gene-1.png and b/reference/vis_gene-1.png differ
diff --git a/reference/vis_gene-10.png b/reference/vis_gene-10.png
index fe1916ef..a44ac448 100644
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diff --git a/reference/vis_gene-2.png b/reference/vis_gene-2.png
index e31f94d3..7da9ccfd 100644
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diff --git a/reference/vis_gene-3.png b/reference/vis_gene-3.png
index ad0dd5f5..e4286c69 100644
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diff --git a/reference/vis_gene-4.png b/reference/vis_gene-4.png
index 55d24ff4..1ff3e170 100644
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diff --git a/reference/vis_gene-5.png b/reference/vis_gene-5.png
index c1e58e44..6cbbe839 100644
Binary files a/reference/vis_gene-5.png and b/reference/vis_gene-5.png differ
diff --git a/reference/vis_gene-6.png b/reference/vis_gene-6.png
index 528c1c2a..9eccafab 100644
Binary files a/reference/vis_gene-6.png and b/reference/vis_gene-6.png differ
diff --git a/reference/vis_gene-7.png b/reference/vis_gene-7.png
index da60a0bf..c26013a0 100644
Binary files a/reference/vis_gene-7.png and b/reference/vis_gene-7.png differ
diff --git a/reference/vis_gene-8.png b/reference/vis_gene-8.png
index 2e73ba4d..a91893cf 100644
Binary files a/reference/vis_gene-8.png and b/reference/vis_gene-8.png differ
diff --git a/reference/vis_gene-9.png b/reference/vis_gene-9.png
index 9123b986..fa2c6a94 100644
Binary files a/reference/vis_gene-9.png and b/reference/vis_gene-9.png differ
diff --git a/reference/vis_gene.html b/reference/vis_gene.html
index e39667fc..f0e49f68 100644
--- a/reference/vis_gene.html
+++ b/reference/vis_gene.html
@@ -66,7 +66,7 @@
@@ -220,12 +220,12 @@ Value
Details
This function subsets spe to the given sample and prepares the
-data and title for vis_gene_p(). It also adds a caption to the plot.
+data and title for vis_gene_p(). It also adds a caption to the plot.
See also
Other Spatial gene visualization functions:
-vis_gene_p(),
+vis_gene_p(),
vis_grid_gene()
@@ -341,8 +341,7 @@ Examples
)
print(p8)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:52:48.10019 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene_p-1.png b/reference/vis_gene_p-1.png
new file mode 100644
index 00000000..24287b46
Binary files /dev/null and b/reference/vis_gene_p-1.png differ
diff --git a/reference/vis_gene_p.html b/reference/vis_gene_p.html
new file mode 100644
index 00000000..4f32d6a8
--- /dev/null
+++ b/reference/vis_gene_p.html
@@ -0,0 +1,245 @@
+
+Sample spatial gene visualization workhorse function — vis_gene_p • spatialLIBD
+
+
+
+
+
+
+
+
+
+
+
+
+ This function visualizes the gene expression stored in assays(spe) or any
+continuous variable stored in colData(spe) for one given sample at the
+spot-level using (by default) the histology information on the background.
+This is the function that does all the plotting behind vis_gene()
+To visualize clusters (or any discrete variable) use vis_clus_p().
+
+
+
+ vis_gene_p(
+ spe,
+ d,
+ sampleid = unique(spe$sample_id)[1],
+ spatial,
+ title,
+ viridis = TRUE,
+ image_id = "lowres",
+ alpha = NA,
+ cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4",
+ "springgreen", "goldenrod", "red"),
+ point_size = 2,
+ auto_crop = TRUE,
+ na_color = "#CCCCCC40",
+ legend_title = ""
+)
+
+
+
+ Arguments
+
+
+- spe
+A
+SpatialExperiment-class
+object. See fetch_data() for how to download some example objects or
+read10xVisiumWrapper() to read in spaceranger --count output files and
+build your own spe object.
- d
+A data.frame() with the sample-level information. This is
+typically obtained using cbind(colData(spe), spatialCoords(spe)).
+The data.frame has to contain
+a column with the continuous variable data to plot stored under d$COUNT.
- sampleid
+A character(1) specifying which sample to plot from
+colData(spe)$sample_id (formerly colData(spe)$sample_name).
- spatial
+A logical(1) indicating whether to include the histology
+layer from geom_spatial(). If you plan to use
+ggplotly() then it's best to set this to FALSE.
- title
+The title for the plot.
- viridis
+A logical(1) whether to use the color-blind friendly
+palette from viridis or the color palette used
+in the paper that was chosen for contrast when visualizing the data on
+top of the histology image. One issue is being able to differentiate low
+values from NA ones due to the purple-ish histology information that is
+dependent on cell density.
- image_id
+A character(1) with the name of the image ID you want to
+use in the background.
- alpha
+A numeric(1) in the [0, 1] range that specifies the
+transparency level of the data on the spots.
- cont_colors
+A character() vector of colors that supersedes the
+viridis argument.
- point_size
+A numeric(1) specifying the size of the points. Defaults
+to 1.25. Some colors look better if you use 2 for instance.
- auto_crop
+A logical(1) indicating whether to automatically crop
+the image / plotting area, which is useful if the Visium capture area is
+not centered on the image and if the image is not a square.
- na_color
+A character(1) specifying a color for the NA values.
+If you set alpha = NA then it's best to set na_color to a color that has
+alpha blending already, which will make non-NA values pop up more and the NA
+values will show with a lighter color. This behavior is lost when alpha is
+set to a non-NA value.
- legend_title
+A character(1) specifying the legend title.
+
+ Value
+ A ggplot2 object.
+
+
+ See also
+ Other Spatial gene visualization functions:
+vis_gene(),
+vis_grid_gene()
+
+
+
+ Examples
+
+if (enough_ram()) {
+ ## Obtain the necessary data
+ if (!exists("spe")) spe <- fetch_data("spe")
+
+ ## Prepare the data for the plotting function
+ spe_sub <- spe[, spe$sample_id == "151673"]
+ df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
+ df$COUNT <- df$expr_chrM_ratio
+
+ ## Don't plot the histology information
+ p <- vis_gene_p(
+ spe = spe_sub,
+ d = df,
+ sampleid = "151673",
+ title = "151673 chrM expr ratio",
+ spatial = FALSE
+ )
+ print(p)
+
+ ## Clean up
+ rm(spe_sub)
+}
+#> 2024-07-17 13:53:14.003193 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/reference/vis_grid_clus-1.png b/reference/vis_grid_clus-1.png
index fc3c2d6c..ea564e20 100644
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diff --git a/reference/vis_grid_clus.html b/reference/vis_grid_clus.html
index beb4cdd7..a1aec073 100644
--- a/reference/vis_grid_clus.html
+++ b/reference/vis_grid_clus.html
@@ -65,7 +65,7 @@
Sample spatial cluster visualization grid
- Source: R/vis_grid_clus.R
+ Source: R/vis_grid_clus.R
vis_grid_clus.Rd
@@ -237,8 +237,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:41.57373 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:29.053452 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_grid_gene-1.png b/reference/vis_grid_gene-1.png
index d8f795d8..b246fec3 100644
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diff --git a/reference/vis_grid_gene.html b/reference/vis_grid_gene.html
index f5428110..7f5c56b0 100644
--- a/reference/vis_grid_gene.html
+++ b/reference/vis_grid_gene.html
@@ -66,7 +66,7 @@
Sample spatial gene visualization grid
- Source: R/vis_grid_gene.R
+ Source: R/vis_grid_gene.R
vis_grid_gene.Rd
@@ -234,7 +234,7 @@ Details
See also
Other Spatial gene visualization functions:
vis_gene(),
-vis_gene_p()
+vis_gene_p()
@@ -256,8 +256,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:53.38865 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:45.486537 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/sitemap.xml b/sitemap.xml
index d4f77066..8a33c15f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -62,6 +62,7 @@
/reference/vis_clus.html /reference/vis_clus_p.html /reference/vis_gene.html /reference/vis_gene_p.html /reference/vis_grid_clus.html /reference/vis_grid_gene.html
spatialLIBD 1.3.3
NEW FEATURES
-- Overall the package has been updated to use
SpatialExperimentversion 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such assce_image_gene_p()now has a shorter namevis_gene_p(). This update also changes these visualization functions to ONLY supportSpatialExperimentobjects instead of the original modifiedSingleCellExperimentobjects.
+ - Overall the package has been updated to use
SpatialExperimentversion 1.1.427 available on Bioconductor 3.13 (bioc-devel). Several functions were re-named such assce_image_gene_p()now has a shorter namevis_gene_p(). This update also changes these visualization functions to ONLY supportSpatialExperimentobjects instead of the original modifiedSingleCellExperimentobjects. - Updated citation information to reflect that https://doi.org/10.1038/s41593-020-00787-0 is now public. Also added a link on the README to https://doi.org/10.6084/m9.figshare.13623902.v1 for the manuscript high resolution images.
Add analysis data from a 10x Genomics Visium experiment to a SPE object
- Source:R/add10xVisiumAnalysis.R
+ Source: R/add10xVisiumAnalysis.R
add10xVisiumAnalysis.RdExamples
if (interactive()) { browseVignettes(package = "spatialLIBD") } -#> No vignettes found by browseVignettes(package = "spatialLIBD") ## Note that ?SpatialExperiment::read10xVisium doesn't include all the files ## we need to illustrate read10xVisiumWrapper(). diff --git a/reference/add_images.html b/reference/add_images.html index 37749b90..db2faadf 100644 --- a/reference/add_images.html +++ b/reference/add_images.html @@ -71,7 +71,7 @@Add non-standard images with the same dimensions as current ones
- Source:R/add_images.R
+ Source: R/add_images.R
add_images.RdExamples
image_paths = c("151507" = "https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151507_tissue_lowres_image.png") )) } -#> snapshotDate(): 2024-04-29 -#> 2024-07-16 17:00:18.72371 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1 -#> 2024-07-16 17:00:29.794628 adding image for sample 151507 -#> 2024-07-16 17:00:30.766353 adding image for sample 151508 +#> 2024-07-17 13:48:26.600477 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1 +#> 2024-07-17 13:48:41.90188 adding image for sample 151507 +#> 2024-07-17 13:48:42.538745 adding image for sample 151508 #> Warning: No image was found for sample: 151508 -#> 2024-07-16 17:00:30.766579 adding image for sample 151509 +#> 2024-07-17 13:48:42.539054 adding image for sample 151509 #> Warning: No image was found for sample: 151509 -#> 2024-07-16 17:00:30.766725 adding image for sample 151510 +#> 2024-07-17 13:48:42.539261 adding image for sample 151510 #> Warning: No image was found for sample: 151510 -#> 2024-07-16 17:00:30.766858 adding image for sample 151669 +#> 2024-07-17 13:48:42.539459 adding image for sample 151669 #> Warning: No image was found for sample: 151669 -#> 2024-07-16 17:00:30.76698 adding image for sample 151670 +#> 2024-07-17 13:48:42.539652 adding image for sample 151670 #> Warning: No image was found for sample: 151670 -#> 2024-07-16 17:00:30.767101 adding image for sample 151671 +#> 2024-07-17 13:48:42.539843 adding image for sample 151671 #> Warning: No image was found for sample: 151671 -#> 2024-07-16 17:00:30.767222 adding image for sample 151672 +#> 2024-07-17 13:48:42.540033 adding image for sample 151672 #> Warning: No image was found for sample: 151672 -#> 2024-07-16 17:00:30.76734 adding image for sample 151673 +#> 2024-07-17 13:48:42.540223 adding image for sample 151673 #> Warning: No image was found for sample: 151673 -#> 2024-07-16 17:00:30.767458 adding image for sample 151674 +#> 2024-07-17 13:48:42.540414 adding image for sample 151674 #> Warning: No image was found for sample: 151674 -#> 2024-07-16 17:00:30.767576 adding image for sample 151675 +#> 2024-07-17 13:48:42.540604 adding image for sample 151675 #> Warning: No image was found for sample: 151675 -#> 2024-07-16 17:00:30.767696 adding image for sample 151676 +#> 2024-07-17 13:48:42.540791 adding image for sample 151676 #> Warning: No image was found for sample: 151676 #> DataFrame with 13 rows and 4 columns #> sample_id image_id data scaleFactor diff --git a/reference/add_key.html b/reference/add_key.html index 7dce6d11..220b5ded 100644 --- a/reference/add_key.html +++ b/reference/add_key.html @@ -65,7 +65,7 @@Examples
spe$key_original <- NULL head(spe$key) } -#> snapshotDate(): 2024-04-29 -#> 2024-07-16 17:00:33.017537 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1 +#> 2024-07-17 13:48:44.910936 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1 #> [1] "151507_AAACAACGAATAGTTC-1" "151507_AAACAAGTATCTCCCA-1" #> [3] "151507_AAACAATCTACTAGCA-1" "151507_AAACACCAATAACTGC-1" #> [5] "151507_AAACAGCTTTCAGAAG-1" "151507_AAACAGGGTCTATATT-1" diff --git a/reference/add_qc_metrics-1.png b/reference/add_qc_metrics-1.png index cade42d4..2e65d510 100644 Binary files a/reference/add_qc_metrics-1.png and b/reference/add_qc_metrics-1.png differ diff --git a/reference/add_qc_metrics-2.png b/reference/add_qc_metrics-2.png index 837a248e..d0142804 100644 Binary files a/reference/add_qc_metrics-2.png and b/reference/add_qc_metrics-2.png differ diff --git a/reference/add_qc_metrics-3.png b/reference/add_qc_metrics-3.png index 479ba97d..2b8c7ead 100644 Binary files a/reference/add_qc_metrics-3.png and b/reference/add_qc_metrics-3.png differ diff --git a/reference/add_qc_metrics-4.png b/reference/add_qc_metrics-4.png index cd287d06..39a4439a 100644 Binary files a/reference/add_qc_metrics-4.png and b/reference/add_qc_metrics-4.png differ diff --git a/reference/add_qc_metrics-5.png b/reference/add_qc_metrics-5.png index e6624e22..e1b6345a 100644 Binary files a/reference/add_qc_metrics-5.png and b/reference/add_qc_metrics-5.png differ diff --git a/reference/add_qc_metrics-6.png b/reference/add_qc_metrics-6.png index 95168130..70357959 100644 Binary files a/reference/add_qc_metrics-6.png and b/reference/add_qc_metrics-6.png differ diff --git a/reference/add_qc_metrics-7.png b/reference/add_qc_metrics-7.png index b21b0b71..0a06596e 100644 Binary files a/reference/add_qc_metrics-7.png and b/reference/add_qc_metrics-7.png differ diff --git a/reference/add_qc_metrics-8.png b/reference/add_qc_metrics-8.png index 41ab0f4e..24a2c0e0 100644 Binary files a/reference/add_qc_metrics-8.png and b/reference/add_qc_metrics-8.png differ diff --git a/reference/add_qc_metrics.html b/reference/add_qc_metrics.html index db6a4d92..9c72a786 100644 --- a/reference/add_qc_metrics.html +++ b/reference/add_qc_metrics.html @@ -67,7 +67,7 @@Quality Control for Spatial Data
- Source:R/add_qc_metrics.R
+ Source: R/add_qc_metrics.R
add_qc_metrics.RdAuthor
Examples
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:43.634355 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f563a40ecf7_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
+#> 2024-07-17 13:49:00.582195 loading file /github/home/.cache/R/BiocFileCache/49872dc0d45_spatialDLPFC_spe_subset_example.rds%3Fdl%3D1
## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
diff --git a/reference/annotate_registered_clusters.html b/reference/annotate_registered_clusters.html
index fd6421d6..50b43af5 100644
--- a/reference/annotate_registered_clusters.html
+++ b/reference/annotate_registered_clusters.html
@@ -67,7 +67,7 @@
Annotated spatially-registered clusters
- Source: R/annotate_registered_clusters.R
+ Source: R/annotate_registered_clusters.R
annotate_registered_clusters.Rd
@@ -137,8 +137,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:51.762523 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:13.326528 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/check_modeling_results.html b/reference/check_modeling_results.html
index e56f7419..f95254df 100644
--- a/reference/check_modeling_results.html
+++ b/reference/check_modeling_results.html
@@ -64,7 +64,7 @@
Check input modeling_results
- Source: R/check_modeling_results.R
+ Source: R/check_modeling_results.R
check_modeling_results.Rd
@@ -108,8 +108,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:52.678188 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:14.441658 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Check the object
xx <- check_modeling_results(modeling_results)
diff --git a/reference/check_sce.html b/reference/check_sce.html
index 8a937cdf..fdc02746 100644
--- a/reference/check_sce.html
+++ b/reference/check_sce.html
@@ -66,7 +66,7 @@
@@ -131,8 +131,7 @@ Examples
## Check the object
check_sce(sce_example)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:53.63802 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1543ff842_sce_sub_for_vignette.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:15.651297 loading file /github/home/.cache/R/BiocFileCache/4982ebeafe0_sce_sub_for_vignette.Rdata%3Fdl%3D1
#> class: SingleCellExperiment
#> dim: 33538 47681
#> metadata(1): image
diff --git a/reference/check_sce_layer.html b/reference/check_sce_layer.html
index e6129283..c926c5cf 100644
--- a/reference/check_sce_layer.html
+++ b/reference/check_sce_layer.html
@@ -64,7 +64,7 @@
Check input sce_layer
- Source: R/check_sce_layer.R
+ Source: R/check_sce_layer.R
check_sce_layer.Rd
@@ -112,8 +112,7 @@ Examples
## Obtain example data from the HumanPilot project
## (Maynard, Collado-Torres, et al, 2021)
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:55.536908 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:18.090538 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Check the pseudo-bulked data
check_sce_layer(sce_layer)
diff --git a/reference/check_spe.html b/reference/check_spe.html
index 00f18aab..262e37d5 100644
--- a/reference/check_spe.html
+++ b/reference/check_spe.html
@@ -64,7 +64,7 @@
@@ -123,8 +123,7 @@ Examples
## Check the object
check_spe(spe)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:00:56.493054 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:19.444343 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> class: SpatialExperiment
#> dim: 33538 47681
#> metadata(0):
diff --git a/reference/cluster_export.html b/reference/cluster_export.html
index 576e5969..41dcf6be 100644
--- a/reference/cluster_export.html
+++ b/reference/cluster_export.html
@@ -67,7 +67,7 @@
Export a column with cluster results
- Source: R/cluster_export.R
+ Source: R/cluster_export.R
cluster_export.Rd
@@ -134,8 +134,7 @@ Examples
cluster_export(spe, "spatialLIBD")
cluster_export(spe, "GraphBased")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:06.836252 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:34.076008 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
diff --git a/reference/cluster_import.html b/reference/cluster_import.html
index feed9a97..585bc91f 100644
--- a/reference/cluster_import.html
+++ b/reference/cluster_import.html
@@ -66,7 +66,7 @@
@@ -137,12 +137,11 @@ Examples
## Re-import them
colData(cluster_import(spe))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:17.501482 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:49:49.230922 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/spatialLIBD' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/spatialLIBD' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
-#> Warning: '/var/folders/_2/hqcmhc1d1bl3lqxgcrkpv8_00000gn/T//RtmpyUe1HH/exported_clusters/GraphBased' already exists
+#> Warning: '/tmp/RtmpCfl3tH/exported_clusters/GraphBased' already exists
#> Overwriting 'spe$key'. Set 'overwrite = FALSE' if you do not want to overwrite it.
#> DataFrame with 47681 rows and 71 columns
#> key sample_id Cluster sum_umi
diff --git a/reference/enough_ram.html b/reference/enough_ram.html
index 1aefe5c0..17fada89 100644
--- a/reference/enough_ram.html
+++ b/reference/enough_ram.html
@@ -63,7 +63,7 @@
Determine if you have enough RAM memory
- Source: R/enough_ram.R
+ Source: R/enough_ram.R
enough_ram.Rd
diff --git a/reference/fetch_data.html b/reference/fetch_data.html
index 860fcc8a..626b28ea 100644
--- a/reference/fetch_data.html
+++ b/reference/fetch_data.html
@@ -71,7 +71,7 @@
Download the Human DLPFC Visium data from LIBD
- Source: R/fetch_data.R
+ Source: R/fetch_data.R
fetch_data.Rd
@@ -166,8 +166,7 @@ Examples
## Download the SingleCellExperiment object
## at the layer-level
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:28.986594 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:04.599487 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Explore the data
sce_layer
diff --git a/reference/frame_limits.html b/reference/frame_limits.html
index 0a945d2b..ce67964f 100644
--- a/reference/frame_limits.html
+++ b/reference/frame_limits.html
@@ -73,7 +73,7 @@
@@ -154,8 +154,7 @@ Examples
## Obtain the frame limits for one sample
frame_limits(spe, sampleid = "151673")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:30.408348 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:07.106212 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> $y_min
#> [1] 64
#>
diff --git a/reference/gene_set_enrichment.html b/reference/gene_set_enrichment.html
index 58358fa3..69f114cc 100644
--- a/reference/gene_set_enrichment.html
+++ b/reference/gene_set_enrichment.html
@@ -68,7 +68,7 @@
Evaluate the enrichment for a list of gene sets
- Source: R/gene_set_enrichment.R
+ Source: R/gene_set_enrichment.R
gene_set_enrichment.Rd
@@ -176,8 +176,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:40.855511 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:21.075222 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/gene_set_enrichment_plot-1.png b/reference/gene_set_enrichment_plot-1.png
index d68b19ec..d366f433 100644
Binary files a/reference/gene_set_enrichment_plot-1.png and b/reference/gene_set_enrichment_plot-1.png differ
diff --git a/reference/gene_set_enrichment_plot-2.png b/reference/gene_set_enrichment_plot-2.png
index 78df31f0..dbc691ef 100644
Binary files a/reference/gene_set_enrichment_plot-2.png and b/reference/gene_set_enrichment_plot-2.png differ
diff --git a/reference/gene_set_enrichment_plot.html b/reference/gene_set_enrichment_plot.html
index 40392d13..ffdc11f2 100644
--- a/reference/gene_set_enrichment_plot.html
+++ b/reference/gene_set_enrichment_plot.html
@@ -64,7 +64,7 @@
Plot the gene set enrichment results
- Source: R/gene_set_enrichment_plot.R
+ Source: R/gene_set_enrichment_plot.R
gene_set_enrichment_plot.Rd
@@ -178,8 +178,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:50:22.531835 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
diff --git a/reference/geom_spatial-1.png b/reference/geom_spatial-1.png
index 64fd3d7a..946c446a 100644
Binary files a/reference/geom_spatial-1.png and b/reference/geom_spatial-1.png differ
diff --git a/reference/geom_spatial.html b/reference/geom_spatial.html
index 5d50b49e..42e5c07c 100644
--- a/reference/geom_spatial.html
+++ b/reference/geom_spatial.html
@@ -66,7 +66,7 @@
A ggplot2 layer for visualizing the Visium histology
- Source: R/geom_spatial.R
+ Source: R/geom_spatial.R
geom_spatial.Rd
@@ -74,7 +74,7 @@ A ggplot2 layer for visualizing the Visium histology
This function defines a ggplot2::layer() for visualizing the histology
image from Visium. It can be combined with other ggplot2 functions for
visualizing the clusters as in vis_clus_p() or gene-level information
-as in vis_gene_p().
+as in vis_gene_p().
@@ -175,8 +175,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
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+#> 2024-07-17 13:50:24.396394 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/get_colors.html b/reference/get_colors.html
index e49a44bf..dfbeb5c2 100644
--- a/reference/get_colors.html
+++ b/reference/get_colors.html
@@ -64,7 +64,7 @@
Obtain the colors for a set of cluster names
- Source: R/get_colors.R
+ Source: R/get_colors.R
get_colors.Rd
@@ -84,7 +84,7 @@ Arguments
- colors
A vector of colors. If NULL then a set of default colors will
be used when clusters has less than 12 unique values, otherwise
-Polychrome::palette36 will be used which can
+Polychrome::palette36 will be used which can
generate up to 36 unique colors. If the number of unique clusters is beyond
36 then this function will fail.
Examples
## Obtain the necessary data
if (!exists("sce_layer")) sce_layer <- fetch_data("sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:01:54.433623 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:39.853193 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Example layer colors with the corresponding names
get_colors(libd_layer_colors, sce_layer$layer_guess)
diff --git a/reference/img_edit-1.png b/reference/img_edit-1.png
index 94154fc3..9af3f312 100644
Binary files a/reference/img_edit-1.png and b/reference/img_edit-1.png differ
diff --git a/reference/img_edit.html b/reference/img_edit.html
index 9df344ec..004b6d82 100644
--- a/reference/img_edit.html
+++ b/reference/img_edit.html
@@ -65,7 +65,7 @@
@@ -222,8 +222,7 @@ Examples
x <- img_edit(spe, sampleid = "151507", brightness = 25)
plot(x)
}
-#> snapshotDate(): 2024-04-29
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diff --git a/reference/img_update.html b/reference/img_update.html
index 5b6a0f39..5d92fe1f 100644
--- a/reference/img_update.html
+++ b/reference/img_update.html
@@ -63,7 +63,7 @@
@@ -139,8 +139,7 @@ Examples
## Reduce brightness to 25% and update the imgData()
imgData(img_update(spe, sampleid = "151507", brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:07.614049 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:50:56.77859 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 13 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/img_update_all.html b/reference/img_update_all.html
index e322e40f..8a0c7996 100644
--- a/reference/img_update_all.html
+++ b/reference/img_update_all.html
@@ -65,7 +65,7 @@
Update the images for all samples
- Source: R/img_update_all.R
+ Source: R/img_update_all.R
img_update_all.Rd
@@ -138,8 +138,7 @@ Examples
## update the imgData()
imgData(img_update_all(spe, brightness = 25))
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:17.633699 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:11.011904 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
#> DataFrame with 24 rows and 4 columns
#> sample_id image_id data scaleFactor
#> <character> <character> <list> <numeric>
diff --git a/reference/index.html b/reference/index.html
index 3d629a4c..fdcce2ae 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -249,6 +249,10 @@ All functions vis_gene()
Sample spatial gene visualization
+
+
+ Sample spatial gene visualization workhorse function
diff --git a/reference/layer_boxplot-1.png b/reference/layer_boxplot-1.png
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index a10d0a22..96e6f0bb 100644
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index 14ac9b54..c8eb3bae 100644
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index f44309f3..5dea49a5 100644
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diff --git a/reference/layer_boxplot.html b/reference/layer_boxplot.html
index 90de61cd..302acf11 100644
--- a/reference/layer_boxplot.html
+++ b/reference/layer_boxplot.html
@@ -65,7 +65,7 @@
Layer-level (group-level) boxplots
- Source: R/layer_boxplot.R
+ Source: R/layer_boxplot.R
layer_boxplot.Rd
@@ -185,11 +185,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:28.442408 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:28.503014 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:29.096088 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:29.384093 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## Top 2 genes from the enrichment model
sig_genes <- sig_genes_extract_all(
diff --git a/reference/layer_matrix_plot-1.png b/reference/layer_matrix_plot-1.png
index d9460395..4f269d7a 100644
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diff --git a/reference/layer_matrix_plot-2.png b/reference/layer_matrix_plot-2.png
index 8e3e7d6d..2f29029a 100644
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diff --git a/reference/layer_matrix_plot.html b/reference/layer_matrix_plot.html
index d2728bb4..d5cd6750 100644
--- a/reference/layer_matrix_plot.html
+++ b/reference/layer_matrix_plot.html
@@ -66,7 +66,7 @@
Visualize a matrix of values across human brain layers
- Source: R/layer_matrix_plot.R
+ Source: R/layer_matrix_plot.R
layer_matrix_plot.Rd
diff --git a/reference/layer_stat_cor.html b/reference/layer_stat_cor.html
index be43eee0..208b193a 100644
--- a/reference/layer_stat_cor.html
+++ b/reference/layer_stat_cor.html
@@ -63,7 +63,7 @@
Layer modeling correlation of statistics
- Source: R/layer_stat_cor.R
+ Source: R/layer_stat_cor.R
layer_stat_cor.Rd
@@ -156,8 +156,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:31.53213 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:32.756558 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/layer_stat_cor_plot-1.png b/reference/layer_stat_cor_plot-1.png
index 5019ec42..72baf49d 100644
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index bdb90ead..d7368ed7 100644
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diff --git a/reference/layer_stat_cor_plot-3.png b/reference/layer_stat_cor_plot-3.png
index c9a9bcf0..4b97784a 100644
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diff --git a/reference/layer_stat_cor_plot-4.png b/reference/layer_stat_cor_plot-4.png
index ee32ca9a..d74ca04c 100644
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diff --git a/reference/layer_stat_cor_plot-5.png b/reference/layer_stat_cor_plot-5.png
index 2e2b880f..a6ca399d 100644
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diff --git a/reference/layer_stat_cor_plot.html b/reference/layer_stat_cor_plot.html
index d08a54a2..7670f03a 100644
--- a/reference/layer_stat_cor_plot.html
+++ b/reference/layer_stat_cor_plot.html
@@ -66,7 +66,7 @@
Visualize the layer modeling correlation of statistics
- Source: R/layer_stat_cor_plot.R
+ Source: R/layer_stat_cor_plot.R
layer_stat_cor_plot.Rd
@@ -145,8 +145,7 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:32.436771 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:33.883339 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
## Compute the correlations
cor_stats_layer <- layer_stat_cor(
diff --git a/reference/libd_layer_colors.html b/reference/libd_layer_colors.html
index d2df282e..6a843fec 100644
--- a/reference/libd_layer_colors.html
+++ b/reference/libd_layer_colors.html
@@ -64,7 +64,7 @@
diff --git a/reference/locate_images.html b/reference/locate_images.html
index 62727198..8cbe293c 100644
--- a/reference/locate_images.html
+++ b/reference/locate_images.html
@@ -65,7 +65,7 @@
diff --git a/reference/multi_gene_pca.html b/reference/multi_gene_pca.html
index 58575a98..334fbe7d 100644
--- a/reference/multi_gene_pca.html
+++ b/reference/multi_gene_pca.html
@@ -68,7 +68,7 @@
Combine multiple continuous variables through PCA
- Source: R/multi_gene_pca.R
+ Source: R/multi_gene_pca.R
multi_gene_pca.Rd
diff --git a/reference/multi_gene_sparsity.html b/reference/multi_gene_sparsity.html
index 042ec2af..2ababa43 100644
--- a/reference/multi_gene_sparsity.html
+++ b/reference/multi_gene_sparsity.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by proportion of positive values
- Source: R/multi_gene_sparsity.R
+ Source: R/multi_gene_sparsity.R
multi_gene_sparsity.Rd
diff --git a/reference/multi_gene_z_score.html b/reference/multi_gene_z_score.html
index 612273f5..ce8a878a 100644
--- a/reference/multi_gene_z_score.html
+++ b/reference/multi_gene_z_score.html
@@ -64,7 +64,7 @@
Combine multiple continuous variables by averaging Z scores
- Source: R/multi_gene_z_score.R
+ Source: R/multi_gene_z_score.R
multi_gene_z_score.Rd
diff --git a/reference/prep_stitched_data.html b/reference/prep_stitched_data.html
index 0c4a592e..36678e3a 100644
--- a/reference/prep_stitched_data.html
+++ b/reference/prep_stitched_data.html
@@ -68,7 +68,7 @@
Prepare stitched data for plotting
- Source: R/prep_stitched_data.R
+ Source: R/prep_stitched_data.R
prep_stitched_data.Rd
diff --git a/reference/read10xVisiumAnalysis.html b/reference/read10xVisiumAnalysis.html
index b36ef451..7e04bd5b 100644
--- a/reference/read10xVisiumAnalysis.html
+++ b/reference/read10xVisiumAnalysis.html
@@ -64,7 +64,7 @@
Load analysis data from a 10x Genomics Visium experiment
- Source: R/read10xVisiumAnalysis.R
+ Source: R/read10xVisiumAnalysis.R
read10xVisiumAnalysis.Rd
@@ -118,7 +118,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/read10xVisiumWrapper.html b/reference/read10xVisiumWrapper.html
index 56b267a0..c8d01991 100644
--- a/reference/read10xVisiumWrapper.html
+++ b/reference/read10xVisiumWrapper.html
@@ -66,7 +66,7 @@
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
- Source: R/read10xVisiumWrapper.R
+ Source: R/read10xVisiumWrapper.R
read10xVisiumWrapper.Rd
@@ -162,7 +162,6 @@ Examples
if (interactive()) {
browseVignettes(package = "spatialLIBD")
}
-#> No vignettes found by browseVignettes(package = "spatialLIBD")
## Note that ?SpatialExperiment::read10xVisium doesn't include all the files
## we need to illustrate read10xVisiumWrapper().
diff --git a/reference/registration_block_cor.html b/reference/registration_block_cor.html
index 33000024..126fabd2 100644
--- a/reference/registration_block_cor.html
+++ b/reference/registration_block_cor.html
@@ -66,7 +66,7 @@
Spatial registration: block correlation
- Source: R/registration_block_cor.R
+ Source: R/registration_block_cor.R
registration_block_cor.Rd
@@ -121,36 +121,36 @@ See also
Examples
example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:34.847415 make pseudobulk object
-#> 2024-07-16 17:02:34.953364 drop lowly expressed genes
-#> 2024-07-16 17:02:34.99097 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:37.088175 make pseudobulk object
+#> 2024-07-17 13:51:37.267087 drop lowly expressed genes
+#> 2024-07-17 13:51:37.336566 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -179,10 +179,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:35.032307 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:37.415555 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -198,8 +198,8 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:35.038484 run duplicateCorrelation()
-#> 2024-07-16 17:02:35.564971 The estimated correlation is: -0.0187869166526901
+#> 2024-07-17 13:51:37.428263 run duplicateCorrelation()
+#> 2024-07-17 13:51:38.691552 The estimated correlation is: -0.0187869166526901
diff --git a/reference/registration_model.html b/reference/registration_model.html
index 7a26252f..c96dc0da 100644
--- a/reference/registration_model.html
+++ b/reference/registration_model.html
@@ -67,7 +67,7 @@
Spatial registration: model
- Source: R/registration_model.R
+ Source: R/registration_model.R
registration_model.Rd
@@ -125,34 +125,34 @@ See also
Examples
example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:35.873124 make pseudobulk object
-#> 2024-07-16 17:02:35.960837 drop lowly expressed genes
-#> 2024-07-16 17:02:35.986325 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:39.129951 make pseudobulk object
+#> 2024-07-17 13:51:39.31554 drop lowly expressed genes
+#> 2024-07-17 13:51:39.370617 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -181,7 +181,7 @@ Examples
#> D_S S D 14
#> E_S S E 11
registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:36.024617 create model matrix
+#> 2024-07-17 13:51:39.447064 create model matrix
head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
diff --git a/reference/registration_pseudobulk.html b/reference/registration_pseudobulk.html
index 653d03b2..8722ef39 100644
--- a/reference/registration_pseudobulk.html
+++ b/reference/registration_pseudobulk.html
@@ -64,7 +64,7 @@
Spatial registration: pseudobulk
- Source: R/registration_pseudobulk.R
+ Source: R/registration_pseudobulk.R
registration_pseudobulk.Rd
@@ -159,9 +159,9 @@ Examples
## Pseudo-bulk
sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.341187 make pseudobulk object
-#> 2024-07-16 17:02:36.4321 drop lowly expressed genes
-#> 2024-07-16 17:02:36.458483 normalize expression
+#> 2024-07-17 13:51:39.903902 make pseudobulk object
+#> 2024-07-17 13:51:40.056716 drop lowly expressed genes
+#> 2024-07-17 13:51:40.111023 normalize expression
colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
diff --git a/reference/registration_stats_anova.html b/reference/registration_stats_anova.html
index 1cf15645..cdc9d765 100644
--- a/reference/registration_stats_anova.html
+++ b/reference/registration_stats_anova.html
@@ -66,7 +66,7 @@
Spatial registration: compute ANOVA statistics
- Source: R/registration_stats_anova.R
+ Source: R/registration_stats_anova.R
registration_stats_anova.Rd
@@ -153,38 +153,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:36.908 make pseudobulk object
-#> 2024-07-16 17:02:36.981269 drop lowly expressed genes
-#> 2024-07-16 17:02:37.007143 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:40.701746 make pseudobulk object
+#> 2024-07-17 13:51:40.884268 drop lowly expressed genes
+#> 2024-07-17 13:51:40.939518 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -213,10 +213,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:37.061168 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:41.012467 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -232,14 +232,14 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:37.066375 run duplicateCorrelation()
-#> 2024-07-16 17:02:37.583667 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:41.024125 run duplicateCorrelation()
+#> 2024-07-17 13:51:42.289985 The estimated correlation is: -0.0187869166526901
results_anova <- registration_stats_anova(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.589856 computing F-statistics
+#> 2024-07-17 13:51:42.302664 computing F-statistics
head(results_anova)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1328075 0.93918553 0.9951876 5.499488 ENSG1 gene1
@@ -254,7 +254,7 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "example"
)
-#> 2024-07-16 17:02:37.615244 computing F-statistics
+#> 2024-07-17 13:51:42.365534 computing F-statistics
head(results_anova_nan)
#> f_stat_example p_value_example fdr_example AveExpr_example ensembl gene
#> 1 0.1357180 0.93736053 0.9943765 5.499488 ENSG1 gene1
@@ -276,7 +276,7 @@ Examples
covars = NULL,
gene_ensembl = "ensembl", gene_name = "gene_name", suffix = "nocovar"
)
-#> 2024-07-16 17:02:37.632809 computing F-statistics
+#> 2024-07-17 13:51:42.415614 computing F-statistics
head(results_anova_nocovar)
#> f_stat_nocovar p_value_nocovar fdr_nocovar AveExpr_nocovar ensembl gene
#> 1 0.1393641 0.9351345 0.9962097 5.499488 ENSG1 gene1
diff --git a/reference/registration_stats_enrichment.html b/reference/registration_stats_enrichment.html
index c2fc717e..b97c7f9c 100644
--- a/reference/registration_stats_enrichment.html
+++ b/reference/registration_stats_enrichment.html
@@ -65,7 +65,7 @@
Spatial registration: compute enrichment statistics
- Source: R/registration_stats_enrichment.R
+ Source: R/registration_stats_enrichment.R
registration_stats_enrichment.Rd
@@ -144,38 +144,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:37.992936 make pseudobulk object
-#> 2024-07-16 17:02:38.06571 drop lowly expressed genes
-#> 2024-07-16 17:02:38.091375 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:42.992514 make pseudobulk object
+#> 2024-07-17 13:51:43.146693 drop lowly expressed genes
+#> 2024-07-17 13:51:43.201202 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -204,10 +204,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:38.129501 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:43.274381 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -223,15 +223,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:38.134799 run duplicateCorrelation()
-#> 2024-07-16 17:02:38.654908 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:43.285637 run duplicateCorrelation()
+#> 2024-07-17 13:51:44.583617 The estimated correlation is: -0.0187869166526901
results_enrichment <- registration_stats_enrichment(sce_pseudo,
block_cor, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.657236 computing enrichment statistics
-#> 2024-07-16 17:02:38.701689 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.587859 computing enrichment statistics
+#> 2024-07-17 13:51:44.705956 extract and reformat enrichment results
head(results_enrichment)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1482017 0.5610669 -0.3612235 -0.3458508 0.88374480 0.58130631
@@ -260,8 +260,8 @@ Examples
block_cor = NaN, "age",
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:38.712787 computing enrichment statistics
-#> 2024-07-16 17:02:38.771541 extract and reformat enrichment results
+#> 2024-07-17 13:51:44.739083 computing enrichment statistics
+#> 2024-07-17 13:51:44.842281 extract and reformat enrichment results
head(results_enrichment_nan)
#> t_stat_G0 t_stat_G1 t_stat_G2M t_stat_S p_value_G0 p_value_G1
#> Gene_0001 0.1497747 0.56711100 -0.3650801 -0.3495404 0.88252049 0.57727506
diff --git a/reference/registration_stats_pairwise.html b/reference/registration_stats_pairwise.html
index c11a5e44..03bff131 100644
--- a/reference/registration_stats_pairwise.html
+++ b/reference/registration_stats_pairwise.html
@@ -66,7 +66,7 @@
Spatial registration: compute pairwise statistics
- Source: R/registration_stats_pairwise.R
+ Source: R/registration_stats_pairwise.R
registration_stats_pairwise.Rd
@@ -146,38 +146,38 @@ See also
Examples
example("registration_block_cor", package = "spatialLIBD")
#>
-#> rgst__devel* > example("registration_model", package = "spatialLIBD")
+#> rgst__> example("registration_model", package = "spatialLIBD")
#>
-#> rgstr_devel* > example("registration_pseudobulk", package = "spatialLIBD")
+#> rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
#>
-#> rgstr_devel* > ## Ensure reproducibility of example data
-#> rgstr_devel* > set.seed(20220907)
+#> rgstr_> ## Ensure reproducibility of example data
+#> rgstr_> set.seed(20220907)
#>
-#> rgstr_devel* > ## Generate example data
-#> rgstr_devel* > sce <- scuttle::mockSCE()
+#> rgstr_> ## Generate example data
+#> rgstr_> sce <- scuttle::mockSCE()
#>
-#> rgstr_devel* > ## Add some sample IDs
-#> rgstr_devel* > sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
+#> rgstr_> ## Add some sample IDs
+#> rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
#>
-#> rgstr_devel* > ## Add a sample-level covariate: age
-#> rgstr_devel* > ages <- rnorm(5, mean = 20, sd = 4)
+#> rgstr_> ## Add a sample-level covariate: age
+#> rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
#>
-#> rgstr_devel* > names(ages) <- LETTERS[1:5]
+#> rgstr_> names(ages) <- LETTERS[1:5]
#>
-#> rgstr_devel* > sce$age <- ages[sce$sample_id]
+#> rgstr_> sce$age <- ages[sce$sample_id]
#>
-#> rgstr_devel* > ## Add gene-level information
-#> rgstr_devel* > rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
+#> rgstr_> ## Add gene-level information
+#> rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
+#> rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
#>
-#> rgstr_devel* > ## Pseudo-bulk
-#> rgstr_devel* > sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
-#> 2024-07-16 17:02:39.085978 make pseudobulk object
-#> 2024-07-16 17:02:39.159736 drop lowly expressed genes
-#> 2024-07-16 17:02:39.185678 normalize expression
+#> rgstr_> ## Pseudo-bulk
+#> rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
+#> 2024-07-17 13:51:45.303165 make pseudobulk object
+#> 2024-07-17 13:51:45.456984 drop lowly expressed genes
+#> 2024-07-17 13:51:45.511196 normalize expression
#>
-#> rgstr_devel* > colData(sce_pseudo)
+#> rgstr_> colData(sce_pseudo)
#> DataFrame with 20 rows and 8 columns
#> Mutation_Status Cell_Cycle Treatment sample_id age
#> <character> <character> <character> <character> <numeric>
@@ -206,10 +206,10 @@ Examples
#> D_S S D 14
#> E_S S E 11
#>
-#> rgstr_devel* > registration_mod <- registration_model(sce_pseudo, "age")
-#> 2024-07-16 17:02:39.224065 create model matrix
+#> rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
+#> 2024-07-17 13:51:45.621594 create model matrix
#>
-#> rgstr_devel* > head(registration_mod)
+#> rgstr_> head(registration_mod)
#> registration_variableG0 registration_variableG1 registration_variableG2M
#> A_G0 1 0 0
#> B_G0 1 0 0
@@ -225,15 +225,15 @@ Examples
#> E_G0 0 20.97006
#> A_G1 0 19.18719
#>
-#> rgst__devel* > block_cor <- registration_block_cor(sce_pseudo, registration_mod)
-#> 2024-07-16 17:02:39.22931 run duplicateCorrelation()
-#> 2024-07-16 17:02:39.781072 The estimated correlation is: -0.0187869166526901
+#> rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
+#> 2024-07-17 13:51:45.632849 run duplicateCorrelation()
+#> 2024-07-17 13:51:46.88774 The estimated correlation is: -0.0187869166526901
results_pairwise <- registration_stats_pairwise(sce_pseudo,
registration_mod, block_cor,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.782515 running the baseline pairwise model
-#> 2024-07-16 17:02:39.790292 computing pairwise statistics
+#> 2024-07-17 13:51:46.889688 running the baseline pairwise model
+#> 2024-07-17 13:51:46.906431 computing pairwise statistics
head(results_pairwise)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2393683 0.29771391 0.28880637 0.5370822 0.5281747
@@ -277,8 +277,8 @@ Examples
block_cor = NaN,
gene_ensembl = "ensembl", gene_name = "gene_name"
)
-#> 2024-07-16 17:02:39.811874 running the baseline pairwise model
-#> 2024-07-16 17:02:39.818697 computing pairwise statistics
+#> 2024-07-17 13:51:46.971696 running the baseline pairwise model
+#> 2024-07-17 13:51:46.989106 computing pairwise statistics
head(results_pairwise_nan)
#> t_stat_G0-G1 t_stat_G0-G2M t_stat_G0-S t_stat_G1-G2M t_stat_G1-S
#> Gene_0001 -0.2419770 0.30095840 0.29195379 0.5429354 0.5339308
diff --git a/reference/registration_wrapper.html b/reference/registration_wrapper.html
index 546b32eb..a04252d2 100644
--- a/reference/registration_wrapper.html
+++ b/reference/registration_wrapper.html
@@ -68,7 +68,7 @@
Spatial registration: wrapper function
- Source: R/registration_wrapper.R
+ Source: R/registration_wrapper.R
registration_wrapper.Rd
@@ -200,18 +200,18 @@ Examples
sce,
"Cell_Cycle", "sample_id", c("age"), "ensembl", "gene_name", "wrapper"
)
-#> 2024-07-16 17:02:40.149028 make pseudobulk object
-#> 2024-07-16 17:02:40.221379 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
-#> 2024-07-16 17:02:40.231996 drop lowly expressed genes
-#> 2024-07-16 17:02:40.27465 normalize expression
-#> 2024-07-16 17:02:40.303232 create model matrix
-#> 2024-07-16 17:02:40.308019 run duplicateCorrelation()
-#> 2024-07-16 17:02:41.300298 The estimated correlation is: -0.0783081238514527
-#> 2024-07-16 17:02:41.301437 computing enrichment statistics
-#> 2024-07-16 17:02:41.342436 extract and reformat enrichment results
-#> 2024-07-16 17:02:41.35071 running the baseline pairwise model
-#> 2024-07-16 17:02:41.357315 computing pairwise statistics
-#> 2024-07-16 17:02:41.380689 computing F-statistics
+#> 2024-07-17 13:51:47.541862 make pseudobulk object
+#> 2024-07-17 13:51:47.707925 dropping 9 pseudo-bulked samples that are below 'min_ncells'.
+#> 2024-07-17 13:51:47.729853 drop lowly expressed genes
+#> 2024-07-17 13:51:47.785167 normalize expression
+#> 2024-07-17 13:51:47.8429 create model matrix
+#> 2024-07-17 13:51:47.853499 run duplicateCorrelation()
+#> 2024-07-17 13:51:50.267571 The estimated correlation is: -0.0783081238514532
+#> 2024-07-17 13:51:50.269845 computing enrichment statistics
+#> 2024-07-17 13:51:50.386595 extract and reformat enrichment results
+#> 2024-07-17 13:51:50.412505 running the baseline pairwise model
+#> 2024-07-17 13:51:50.430847 computing pairwise statistics
+#> 2024-07-17 13:51:50.505218 computing F-statistics
diff --git a/reference/run_app.html b/reference/run_app.html
index d23cb924..2cca4ddc 100644
--- a/reference/run_app.html
+++ b/reference/run_app.html
@@ -65,7 +65,7 @@
@@ -270,7 +270,7 @@ Examples
vars <- colnames(colData(spe))
## Set default cluster colors
- colors_BayesSpace <- Polychrome::palette36.colors(28)
+ colors_BayesSpace <- Polychrome::palette36.colors(28)
names(colors_BayesSpace) <- c(1:28)
m <- match(as.character(spe$BayesSpace_harmony_09), names(colors_BayesSpace))
stopifnot(all(!is.na(m)))
diff --git a/reference/sce_to_spe.html b/reference/sce_to_spe.html
index 84fd3093..e0797fb6 100644
--- a/reference/sce_to_spe.html
+++ b/reference/sce_to_spe.html
@@ -67,7 +67,7 @@
@@ -127,8 +127,7 @@ Examples
## Transform it to a SpatialExperiment object
spe <- sce_to_spe(sce)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:43.103369 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:51:52.727073 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/sig_genes_extract.html b/reference/sig_genes_extract.html
index 0ecdbcc3..4c448c85 100644
--- a/reference/sig_genes_extract.html
+++ b/reference/sig_genes_extract.html
@@ -67,7 +67,7 @@
Extract significant genes
- Source: R/sig_genes_extract.R
+ Source: R/sig_genes_extract.R
sig_genes_extract.Rd
@@ -156,11 +156,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:52.484674 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:05.714888 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:53.182388 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:06.659035 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## anova top 10 genes
sig_genes_extract(
diff --git a/reference/sig_genes_extract_all.html b/reference/sig_genes_extract_all.html
index 17516a57..4a42f61e 100644
--- a/reference/sig_genes_extract_all.html
+++ b/reference/sig_genes_extract_all.html
@@ -65,7 +65,7 @@
Extract significant genes for all modeling results
- Source: R/sig_genes_extract_all.R
+ Source: R/sig_genes_extract_all.R
sig_genes_extract_all.Rd
@@ -128,11 +128,9 @@ Examples
if (!exists("modeling_results")) {
modeling_results <- fetch_data(type = "modeling_results")
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.422915 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc154f26894b_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:10.311903 loading file /github/home/.cache/R/BiocFileCache/4981423d30a_Human_DLPFC_Visium_modeling_results.Rdata%3Fdl%3D1
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:55.970561 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/fc1571d8e1fb_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:11.371345 loading file /github/home/.cache/R/BiocFileCache/4987a2d0cae_Human_DLPFC_Visium_processedData_sce_scran_sce_layer_spatialLIBD.Rdata%3Fdl%3D1
## top 10 genes for all models
sig_genes_extract_all(
diff --git a/reference/sort_clusters.html b/reference/sort_clusters.html
index 8dccd3d7..675c4397 100644
--- a/reference/sort_clusters.html
+++ b/reference/sort_clusters.html
@@ -65,7 +65,7 @@
diff --git a/reference/spatialLIBD-package.html b/reference/spatialLIBD-package.html
index 148e52f3..c22a18c2 100644
--- a/reference/spatialLIBD-package.html
+++ b/reference/spatialLIBD-package.html
@@ -64,7 +64,7 @@
spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
- Source: R/spatialLIBD-package.R
+ Source: R/spatialLIBD-package.R
spatialLIBD-package.Rd
diff --git a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
index e6a4ba86..4dbbeb2a 100644
--- a/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
+++ b/reference/tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.html
@@ -69,7 +69,7 @@
Cell cluster t-statistics from Tran et al
- Source: R/data.R
+ Source: R/data.R
tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer.Rd
diff --git a/reference/vis_clus-1.png b/reference/vis_clus-1.png
index b62ae3bc..fff9298e 100644
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diff --git a/reference/vis_clus-2.png b/reference/vis_clus-2.png
index 59f18aa4..4962aaef 100644
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diff --git a/reference/vis_clus-3.png b/reference/vis_clus-3.png
index ac93117a..3a3d3926 100644
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diff --git a/reference/vis_clus-4.png b/reference/vis_clus-4.png
index 7a08ba8a..fd74eca4 100644
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diff --git a/reference/vis_clus.html b/reference/vis_clus.html
index 4c441931..29b47fed 100644
--- a/reference/vis_clus.html
+++ b/reference/vis_clus.html
@@ -65,7 +65,7 @@
@@ -242,8 +242,7 @@ Examples
)
print(p4)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:02:57.892758 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:14.053539 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_clus_p-1.png b/reference/vis_clus_p-1.png
index ac93117a..3a3d3926 100644
Binary files a/reference/vis_clus_p-1.png and b/reference/vis_clus_p-1.png differ
diff --git a/reference/vis_clus_p.html b/reference/vis_clus_p.html
index 0106b4be..1e416396 100644
--- a/reference/vis_clus_p.html
+++ b/reference/vis_clus_p.html
@@ -66,7 +66,7 @@
Sample spatial cluster visualization workhorse function
- Source: R/vis_clus_p.R
+ Source: R/vis_clus_p.R
vis_clus_p.Rd
@@ -74,7 +74,7 @@ Sample spatial cluster visualization workhorse function
This function visualizes the clusters for one given sample at the spot-level
using (by default) the histology information on the background. This is the
function that does all the plotting behind vis_clus(). To visualize
-gene-level (or any continuous variable) use vis_gene_p().
+gene-level (or any continuous variable) use vis_gene_p().
@@ -202,8 +202,7 @@ Examples
## Clean up
rm(spe_sub)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:12.064384 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:33.265544 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene-1.png b/reference/vis_gene-1.png
index dd3f3f08..3585ea9b 100644
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diff --git a/reference/vis_gene-10.png b/reference/vis_gene-10.png
index fe1916ef..a44ac448 100644
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diff --git a/reference/vis_gene-2.png b/reference/vis_gene-2.png
index e31f94d3..7da9ccfd 100644
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diff --git a/reference/vis_gene-3.png b/reference/vis_gene-3.png
index ad0dd5f5..e4286c69 100644
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diff --git a/reference/vis_gene-4.png b/reference/vis_gene-4.png
index 55d24ff4..1ff3e170 100644
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diff --git a/reference/vis_gene-5.png b/reference/vis_gene-5.png
index c1e58e44..6cbbe839 100644
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diff --git a/reference/vis_gene-6.png b/reference/vis_gene-6.png
index 528c1c2a..9eccafab 100644
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diff --git a/reference/vis_gene-7.png b/reference/vis_gene-7.png
index da60a0bf..c26013a0 100644
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diff --git a/reference/vis_gene-8.png b/reference/vis_gene-8.png
index 2e73ba4d..a91893cf 100644
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diff --git a/reference/vis_gene-9.png b/reference/vis_gene-9.png
index 9123b986..fa2c6a94 100644
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diff --git a/reference/vis_gene.html b/reference/vis_gene.html
index e39667fc..f0e49f68 100644
--- a/reference/vis_gene.html
+++ b/reference/vis_gene.html
@@ -66,7 +66,7 @@
@@ -220,12 +220,12 @@ Value
Details
This function subsets spe to the given sample and prepares the
-data and title for vis_gene_p(). It also adds a caption to the plot.
+data and title for vis_gene_p(). It also adds a caption to the plot.
See also
Other Spatial gene visualization functions:
-vis_gene_p(),
+vis_gene_p(),
vis_grid_gene()
@@ -341,8 +341,7 @@ Examples
)
print(p8)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:22.728238 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:52:48.10019 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_gene_p-1.png b/reference/vis_gene_p-1.png
new file mode 100644
index 00000000..24287b46
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diff --git a/reference/vis_gene_p.html b/reference/vis_gene_p.html
new file mode 100644
index 00000000..4f32d6a8
--- /dev/null
+++ b/reference/vis_gene_p.html
@@ -0,0 +1,245 @@
+
+Sample spatial gene visualization workhorse function — vis_gene_p • spatialLIBD
+
+
+
+
+
+
+
+
+
+
+
+
+ This function visualizes the gene expression stored in assays(spe) or any
+continuous variable stored in colData(spe) for one given sample at the
+spot-level using (by default) the histology information on the background.
+This is the function that does all the plotting behind vis_gene()
+To visualize clusters (or any discrete variable) use vis_clus_p().
+
+
+
+ vis_gene_p(
+ spe,
+ d,
+ sampleid = unique(spe$sample_id)[1],
+ spatial,
+ title,
+ viridis = TRUE,
+ image_id = "lowres",
+ alpha = NA,
+ cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4",
+ "springgreen", "goldenrod", "red"),
+ point_size = 2,
+ auto_crop = TRUE,
+ na_color = "#CCCCCC40",
+ legend_title = ""
+)
+
+
+
+ Arguments
+
+
+- spe
+A
+SpatialExperiment-class
+object. See fetch_data() for how to download some example objects or
+read10xVisiumWrapper() to read in spaceranger --count output files and
+build your own spe object.
- d
+A data.frame() with the sample-level information. This is
+typically obtained using cbind(colData(spe), spatialCoords(spe)).
+The data.frame has to contain
+a column with the continuous variable data to plot stored under d$COUNT.
- sampleid
+A character(1) specifying which sample to plot from
+colData(spe)$sample_id (formerly colData(spe)$sample_name).
- spatial
+A logical(1) indicating whether to include the histology
+layer from geom_spatial(). If you plan to use
+ggplotly() then it's best to set this to FALSE.
- title
+The title for the plot.
- viridis
+A logical(1) whether to use the color-blind friendly
+palette from viridis or the color palette used
+in the paper that was chosen for contrast when visualizing the data on
+top of the histology image. One issue is being able to differentiate low
+values from NA ones due to the purple-ish histology information that is
+dependent on cell density.
- image_id
+A character(1) with the name of the image ID you want to
+use in the background.
- alpha
+A numeric(1) in the [0, 1] range that specifies the
+transparency level of the data on the spots.
- cont_colors
+A character() vector of colors that supersedes the
+viridis argument.
- point_size
+A numeric(1) specifying the size of the points. Defaults
+to 1.25. Some colors look better if you use 2 for instance.
- auto_crop
+A logical(1) indicating whether to automatically crop
+the image / plotting area, which is useful if the Visium capture area is
+not centered on the image and if the image is not a square.
- na_color
+A character(1) specifying a color for the NA values.
+If you set alpha = NA then it's best to set na_color to a color that has
+alpha blending already, which will make non-NA values pop up more and the NA
+values will show with a lighter color. This behavior is lost when alpha is
+set to a non-NA value.
- legend_title
+A character(1) specifying the legend title.
+
+ Value
+ A ggplot2 object.
+
+
+ See also
+ Other Spatial gene visualization functions:
+vis_gene(),
+vis_grid_gene()
+
+
+
+ Examples
+
+if (enough_ram()) {
+ ## Obtain the necessary data
+ if (!exists("spe")) spe <- fetch_data("spe")
+
+ ## Prepare the data for the plotting function
+ spe_sub <- spe[, spe$sample_id == "151673"]
+ df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
+ df$COUNT <- df$expr_chrM_ratio
+
+ ## Don't plot the histology information
+ p <- vis_gene_p(
+ spe = spe_sub,
+ d = df,
+ sampleid = "151673",
+ title = "151673 chrM expr ratio",
+ spatial = FALSE
+ )
+ print(p)
+
+ ## Clean up
+ rm(spe_sub)
+}
+#> 2024-07-17 13:53:14.003193 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/reference/vis_grid_clus-1.png b/reference/vis_grid_clus-1.png
index fc3c2d6c..ea564e20 100644
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diff --git a/reference/vis_grid_clus.html b/reference/vis_grid_clus.html
index beb4cdd7..a1aec073 100644
--- a/reference/vis_grid_clus.html
+++ b/reference/vis_grid_clus.html
@@ -65,7 +65,7 @@
Sample spatial cluster visualization grid
- Source: R/vis_grid_clus.R
+ Source: R/vis_grid_clus.R
vis_grid_clus.Rd
@@ -237,8 +237,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:41.57373 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:29.053452 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/reference/vis_grid_gene-1.png b/reference/vis_grid_gene-1.png
index d8f795d8..b246fec3 100644
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diff --git a/reference/vis_grid_gene.html b/reference/vis_grid_gene.html
index f5428110..7f5c56b0 100644
--- a/reference/vis_grid_gene.html
+++ b/reference/vis_grid_gene.html
@@ -66,7 +66,7 @@
Sample spatial gene visualization grid
- Source: R/vis_grid_gene.R
+ Source: R/vis_grid_gene.R
vis_grid_gene.Rd
@@ -234,7 +234,7 @@ Details
See also
Other Spatial gene visualization functions:
vis_gene(),
-vis_gene_p()
+vis_gene_p()
@@ -256,8 +256,7 @@ Examples
## for subject 3
cowplot::plot_grid(plotlist = p_list, ncol = 2)
}
-#> snapshotDate(): 2024-04-29
-#> 2024-07-16 17:03:53.38865 loading file /Users/leocollado/Library/Caches/org.R-project.R/R/BiocFileCache/6f56656adcb_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
+#> 2024-07-17 13:53:45.486537 loading file /github/home/.cache/R/BiocFileCache/f66381e3f71_Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata%3Fdl%3D1
diff --git a/sitemap.xml b/sitemap.xml
index d4f77066..8a33c15f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -62,6 +62,7 @@
/reference/vis_clus.html /reference/vis_clus_p.html /reference/vis_gene.html /reference/vis_gene_p.html /reference/vis_grid_clus.html /reference/vis_grid_gene.html