From c32b6910285372a8968a5f12b54441384c3dc184 Mon Sep 17 00:00:00 2001 From: HediaTnani <59562743+HediaTnani@users.noreply.github.com> Date: Wed, 3 Jan 2024 21:32:26 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20LieberIn?= =?UTF-8?q?stitute/qsvaR@7a2e149a8bbfbdfe7dd529144e8cbd4d95a9e16f=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- articles/Intro_qsvaR.html | 243 +++++++++++++++++++------------------- authors.html | 8 +- index.html | 1 - pkgdown.yml | 4 +- 4 files changed, 130 insertions(+), 126 deletions(-) diff --git a/articles/Intro_qsvaR.html b/articles/Intro_qsvaR.html index 27aae75..e005a5e 100644 --- a/articles/Intro_qsvaR.html +++ b/articles/Intro_qsvaR.html @@ -99,7 +99,7 @@
vignettes/Intro_qsvaR.Rmd
Intro_qsvaR.Rmd
qsvaR
R
is an open-source statistical environment which can be
-easily modified to enhance its functionality via packages. qsvaR is a
+easily modified to enhance its functionality via packages. qsvaR is a
R
package available via the Bioconductor repository for packages.
R
can be installed on any operating system from CRAN after which you can install
-qsvaR by
+qsvaR by
using the following commands in your R
session:
## To install Bioconductor packages
@@ -137,10 +137,10 @@ Install qsvaR
Required knowledge
-qsvaR is
+
qsvaR is
based on many other packages and in particular in those that have
implemented the infrastructure needed for dealing with RNA-seq data.
-That is, packages like SummarizedExperiment.
+That is, packages like SummarizedExperiment.
Here it might be useful for you to check the qSVA framework manuscript
(Jaffe et al, PNAS,
2017).
@@ -168,7 +168,7 @@ Asking for help
Citing qsvaR
-We hope that qsvaR will
+
We hope that qsvaR will
be useful for your research. Please use the following information to
cite the package and the overall approach. Thank you!
@@ -176,12 +176,12 @@ Citing qsvaR
citation("qsvaR")
#> To cite package 'qsvaR' in publications use:
#>
-#> Stolz JM, Tnani H, Collado-Torres L (2023). _qsvaR_.
+#> Stolz JM, Tnani H, Collado-Torres L (2024). _qsvaR_.
#> doi:10.18129/B9.bioc.qsvaR <https://doi.org/10.18129/B9.bioc.qsvaR>,
#> https://github.com/LieberInstitute/qsvaR/qsvaR - R package version
#> 1.5.3, <http://www.bioconductor.org/packages/qsvaR>.
#>
-#> Stolz JM, Tnani H, Tao R, Jaffe AE, Collado-Torres L (2023). "qsvaR."
+#> Stolz JM, Tnani H, Tao R, Jaffe AE, Collado-Torres L (2024). "qsvaR."
#> _bioRxiv_. doi:10.1101/TODO <https://doi.org/10.1101/TODO>,
#> <https://www.biorxiv.org/content/10.1101/TODO>.
#>
@@ -230,8 +230,8 @@ Significant Transcripts
-The qsvaR
-(Stolz, Tnani, and Collado-Torres, 2023) package combines an established
+
The qsvaR
+(Stolz, Tnani, and Collado-Torres, 2024) package combines an established
method for removing the effects of degradation from RNA-seq data with
easy to use functions. The first step in this workflow is to create an
RangedSummarizedExperiment
@@ -430,7 +430,7 @@
Differential ExpressionclusterProfiler.
+such as clusterProfiler.
# get expression for most significant gene
yy <- txExprs[rownames(txExprs) == rownames(sigTx)[1], ]
@@ -522,13 +522,13 @@ Differential ExpressionConclusion
We have shown that this method is effective for removing the effects
-of degradation from RNA-seq data. We found that the qsvaR is
+of degradation from RNA-seq data. We found that the qsvaR is
simpler to use than the previous version from 2016 that used expressed
regions instead of transcripts making this software package preferable
for users. I would encourage users to read how each set of degradation
transcripts was selected as not all models may be appropriate for every
-experiment. Thank you for your interest and for using qsvaR
-(Stolz, Tnani, and Collado-Torres, 2023)!
+experiment. Thank you for your interest and for using qsvaR
+(Stolz, Tnani, and Collado-Torres, 2024)!
Acknowledgements
@@ -537,11 +537,11 @@ Acknowledgements
Heena Divecha for
-proofreading the documentation of qsvaR
+proofreading the documentation of qsvaR
Louise A. Huuki-Myers for
-guidance with understanding R code and editing qsvaR
+guidance with understanding R code and editing qsvaR
Nicholas J. Eagles for
@@ -549,23 +549,23 @@ Acknowledgements
Aja Hope for
-proofreading the documentation of qsvaR
+proofreading the documentation of qsvaR
Reproducibility
-The qsvaR
-package (Stolz, Tnani, and Collado-Torres, 2023) was made possible
+
The qsvaR
+package (Stolz, Tnani, and Collado-Torres, 2024) was made possible
thanks to:
- R (R Core Team, 2023)
-
-BiocFileCache
+BiocFileCache
(Shepherd and Morgan, 2023)
-
-BiocStyle
+BiocStyle
(Oleś, 2023)
-
covr
@@ -577,7 +577,7 @@
Reproducibilityknitr (Xie,
2023)
-
-limma
+limma
(Ritchie, Phipson, Wu, Hu, Law, Shi, and Smyth, 2015)
-
RefManageR
@@ -593,13 +593,13 @@
Reproducibilitytestthat
(Wickham, 2011)
-
-SummarizedExperiment
+SummarizedExperiment
(Morgan, Obenchain, Hester, and Pagès, 2023)
-
-sva (Leek,
+sva (Leek,
Johnson, Parker, Fertig, Jaffe, Zhang, Storey, and Torres, 2023)
-This package was developed using biocthis.
+This package was developed using biocthis.
Code for creating the vignette
## Create the vignette
@@ -610,133 +610,135 @@ Reproducibilitylibrary("knitr")
knit("Intro_qsvaR.Rmd", tangle = TRUE)
Date the vignette was generated.
-#> [1] "2023-06-27 14:22:20 UTC"
+#> [1] "2024-01-03 21:32:13 UTC"
Wallclock time spent generating the vignette.
-#> Time difference of 1.653 mins
+#> Time difference of 1.095 mins
R
session information.
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#> language en
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz UTC
-#> date 2023-06-27
-#> pandoc 2.19.2 @ /usr/local/bin/ (via rmarkdown)
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@@ -747,7 +749,7 @@ Reproducibility
Bibliography
-This vignette was generated using BiocStyle
+
This vignette was generated using BiocStyle
(Oleś, 2023) with knitr (Xie,
2023) and rmarkdown
(Allaire, Xie, Dervieux et al., 2023) running behind the scenes.
@@ -756,17 +758,19 @@ Bibliography[1]
J. Allaire, Y. Xie, C. Dervieux, et al. rmarkdown: Dynamic Documents
-for R. R package version 2.22. 2023. URL:
+for R. R package version 2.25. 2023. URL:
https://github.com/rstudio/rmarkdown.
[2]
-J. Hester. covr: Test Coverage for Packages. https://covr.r-lib.org, https://github.com/r-lib/covr. 2023.
+J. Hester. covr: Test Coverage for Packages. R package version
+3.6.4, https://github.com/r-lib/covr. 2023. URL:
+https://covr.r-lib.org.
[3]
J. T. Leek, W. E. Johnson, H. S. Parker, et al. sva: Surrogate
-Variable Analysis. R package version 3.48.0. 2023. DOI:
+Variable Analysis. R package version 3.50.0. 2023. DOI:
10.18129/B9.bioc.sva.
URL:
https://bioconductor.org/packages/sva.
@@ -781,7 +785,7 @@
Bibliography[5]
M. Morgan, V. Obenchain, J. Hester, et al. SummarizedExperiment:
-SummarizedExperiment container. R package version 1.30.2. 2023.
+SummarizedExperiment container. R package version 1.32.0. 2023.
DOI:
10.18129/B9.bioc.SummarizedExperiment.
URL:
@@ -790,7 +794,7 @@ Bibliography[6]
A. Oleś. BiocStyle: Standard styles for vignettes and other
-Bioconductor documents. R package version 2.28.0. 2023. DOI:
+Bioconductor documents. R package version 2.30.0. 2023. DOI:
10.18129/B9.bioc.BiocStyle.
URL:
https://bioconductor.org/packages/BiocStyle.
@@ -812,15 +816,15 @@ Bibliography[9]
L. Shepherd and M. Morgan. BiocFileCache: Manage Files Across
-Sessions. R package version 2.8.0. 2023. DOI:
+Sessions. R package version 2.10.1. 2023. DOI:
10.18129/B9.bioc.BiocFileCache.
URL:
https://bioconductor.org/packages/BiocFileCache.
-[10]
+[10]
J. M. Stolz, H. Tnani, and L. Collado-Torres. qsvaR. https://github.com/LieberInstitute/qsvaR/qsvaR - R
-package version 1.5.3. 2023. DOI:
+package version 1.5.3. 2024. DOI:
10.18129/B9.bioc.qsvaR.
URL:
http://www.bioconductor.org/packages/qsvaR.
@@ -840,12 +844,13 @@ Bibliography[13]
H. Wickham, W. Chang, R. Flight, et al. sessioninfo: R Session
-Information. https://github.com/r-lib/sessioninfo#readme, https://r-lib.github.io/sessioninfo/. 2021.
+Information. R package version 1.2.2, https://r-lib.github.io/sessioninfo/. 2021. URL:
+https://github.com/r-lib/sessioninfo#readme.
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Y. Xie. knitr: A General-Purpose Package for Dynamic Report
-Generation in R. R package version 1.43. 2023. URL:
+Generation in R. R package version 1.45. 2023. URL:
https://yihui.org/knitr/.
diff --git a/authors.html b/authors.html
index 243711b..336f1c4 100644
--- a/authors.html
+++ b/authors.html
@@ -79,19 +79,19 @@ Citation
Stolz JM, Tnani H, Collado-Torres L (2023). +
Stolz JM, Tnani H, Collado-Torres L (2024). qsvaR. doi:10.18129/B9.bioc.qsvaR, https://github.com/LieberInstitute/qsvaR/qsvaR - R package version 1.5.3, http://www.bioconductor.org/packages/qsvaR.
@Manual{, title = {qsvaR}, author = {Joshua M. Stolz and Hedia Tnani and Leonardo Collado-Torres}, - year = {2023}, + year = {2024}, url = {http://www.bioconductor.org/packages/qsvaR}, note = {https://github.com/LieberInstitute/qsvaR/qsvaR - R package version 1.5.3}, doi = {10.18129/B9.bioc.qsvaR}, }-
Stolz JM, Tnani H, Tao R, Jaffe AE, Collado-Torres L (2023). +
Stolz JM, Tnani H, Tao R, Jaffe AE, Collado-Torres L (2024). “qsvaR.” bioRxiv. doi:10.1101/TODO, https://www.biorxiv.org/content/10.1101/TODO. @@ -99,7 +99,7 @@
@Article{, title = {qsvaR}, author = {Joshua M. Stolz and Hedia Tnani and Ran Tao and Andrew E. Jaffe and Leonardo Collado-Torres}, - year = {2023}, + year = {2024}, journal = {bioRxiv}, doi = {10.1101/TODO}, url = {https://www.biorxiv.org/content/10.1101/TODO}, diff --git a/index.html b/index.html index c5f2b71..008592e 100644 --- a/index.html +++ b/index.html @@ -240,7 +240,6 @@Differential Expression
Links
diff --git a/pkgdown.yml b/pkgdown.yml index 4226c59..7be623d 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -1,7 +1,7 @@ -pandoc: 2.19.2 +pandoc: 3.1.1 pkgdown: 2.0.7 pkgdown_sha: ~ articles: Intro_qsvaR: Intro_qsvaR.html -last_built: 2023-06-27T14:20Z +last_built: 2024-01-03T21:30Z