brca_tcga_pan_can_atlas_2018 is failing with cBioDataPack
#68
Comments
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Hi @mjsteinbaugh |
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Thanks @LiNk-NY I'll file a bug there too |
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Following up, I agree that it's better to fix the upstream source, but it does look like readr handles this file OK. library(pipette)
con <- "https://github.com/cBioPortal/datahub/raw/master/public/brca_tcga_pan_can_atlas_2018/data_sv.txt"
## Errors, as expected.
sv_base <- import(
con = con,
format = "tsv",
colnames = TRUE
)
## Error in (function (file, header = FALSE, sep = "", quote = "\"'", dec = ".", :
## more columns than column names
## Calls: import ... import -> .local -> do.call -> do.call -> <Anonymous>
## Munges the number of columns and names, not great.
sv_dt <- import(
con = con,
format = "tsv",
engine = "data.table",
colnames = TRUE
)
print(dim(sv_dt))
## [1] 5335 17
## The readr/vroom engine seems to parse OK.
sv_readr <- import(
con = con,
format = "tsv",
engine = "readr",
colnames = TRUE
)
print(dim(sv_readr))
## [1] 5336 13
print(colnames(sv_readr))
## [1] "Sample_Id" "Site1_Hugo_Symbol"
## [3] "Site1_Chromosome" "Site1_Position"
## [5] "Site2_Hugo_Symbol" "Site2_Chromosome"
## [7] "Site2_Position" "Site2_Effect_On_Frame"
## [9] "Tumor_Split_Read_Count" "Tumor_Paired_End_Read_Count"
## [11] "SV_Status" "NCBI_Build"
## [13] "Event_Info" |
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OK issue has been filed with the cBioPortal datahub team here cBioPortal/datahub#1820 |
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I can confirm that fixing the ## First, replace the `data_sv.txt` file in extracted directory.
object <- cBioPortalData::loadStudy("brca_tcga_pan_can_atlas_2018", cleanup = FALSE)
## A MultiAssayExperiment object of 18 listed
## experiments with user-defined names and respective classes.
## Containing an ExperimentList class object of length 18:
## [1] armlevel_cna: SummarizedExperiment with 39 rows and 1084 columns
## [2] cna_hg19.seg: RaggedExperiment with 210376 rows and 1068 columns
## [3] cna: SummarizedExperiment with 25128 rows and 1070 columns
## [4] log2_cna: SummarizedExperiment with 25128 rows and 1070 columns
## [5] methylation_hm27_hm450_merged: SummarizedExperiment with 22601 rows and 1066 columns
## [6] microbiome: SummarizedExperiment with 1406 rows and 1070 columns
## [7] mrna_seq_v2_rsem_zscores_ref_all_samples: SummarizedExperiment with 20531 rows and 1082 columns
## [8] mrna_seq_v2_rsem_zscores_ref_diploid_samples: SummarizedExperiment with 20471 rows and 1082 columns
## [9] mrna_seq_v2_rsem_zscores_ref_normal_samples: SummarizedExperiment with 20531 rows and 1082 columns
## [10] mrna_seq_v2_rsem: SummarizedExperiment with 20531 rows and 1082 columns
## [11] mutations: RaggedExperiment with 130495 rows and 1009 columns
## [12] phosphoprotein_quantification: SummarizedExperiment with 18806 rows and 105 columns
## [13] protein_quantification_zscores: SummarizedExperiment with 9733 rows and 105 columns
## [14] protein_quantification: SummarizedExperiment with 9733 rows and 105 columns
## [15] rppa_zscores: SummarizedExperiment with 198 rows and 876 columns
## [16] rppa: SummarizedExperiment with 198 rows and 876 columns
## [17] mrna_seq_v2_rsem_normal_samples_zscores_ref_normal_samples: SummarizedExperiment with 20531 rows and 114 columns
## [18] mrna_seq_v2_rsem_normal_samples: SummarizedExperiment with 20531 rows and 114 columns
## Functionality:
## experiments() - obtain the ExperimentList instance
## colData() - the primary/phenotype DataFrame
## sampleMap() - the sample coordination DataFrame
## `$`, `[`, `[[` - extract colData columns, subset, or experiment
## *Format() - convert into a long or wide DataFrame
## assays() - convert ExperimentList to a SimpleList of matrices
## exportClass() - save data to flat files |
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Seeing parsing issues for:
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Thanks for putting this together @mjsteinbaugh |
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@LiNk-NY I put together a pretty nifty script that attempts to process all of the datasets at cBioPortal. I'll update the list of failures here once it finishes running. |
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Draft functions are here for reference: |
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@mjsteinbaugh |
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OK here's an updated list of datasets with processing issues: |
Hi, I'm seeing a parsing error for
brca_tcga_pan_can_atlas_2018:utils::read.tablechokes too easily on malformed files -- is it worth considering switching to readr/vroom or data.table here to harden against malformed files in the tarballs?The text was updated successfully, but these errors were encountered: