Manually download, untar, and load study tarballs

Note that these functions should be used when a particular study is not currently available as a MultiAssayExperiment representation. Otherwise, use cBioDataPack. Provide a cancer_study_id from getStudies and retrieve the study tarball from the cBio Genomics Portal. These functions are used by cBioDataPack under the hood to download,untar, and load the tarball datasets with caching. As stated in ?cBioDataPack, not all studies are currently working as MultiAssayExperiment objects. As of July 2020, about ~80% of datasets can be successfully imported into the MultiAssayExperiment data class. Please open an issue if you would like the team to prioritize a study. You may also check getStudies(buildReport = TRUE)$pack_build for the current status.

Usage

downloadStudy(
  cancer_study_id,
  use_cache = TRUE,
  force = FALSE,
  url_location = getOption("cBio_URL", .url_location),
  ask = interactive()
)

untarStudy(cancer_study_file, exdir = tempdir())

loadStudy(
  filepath,
  names.field = c("Hugo_Symbol", "Entrez_Gene_Id", "Gene", "Composite.Element.REF"),
  cleanup = TRUE
)

Arguments

cancer_study_id: character(1) The study identifier from cBioPortal as seen in the dataset links at https://www.cbioportal.org/datasets.
use_cache: logical(1) (default TRUE) create the default cache location and use it to track downloaded data. If data found in the cache, data will not be re-downloaded. A path can also be provided to data cache location.
force: logical(1) (default FALSE) whether to force re-download data from remote location
url_location: character(1) (default "https://cbioportal-datahub.s3.amazonaws.com") the URL location for downloading packaged data. Can be set using the 'cBio_URL' option (see ?cBioDataPack for more details)
ask: logical(1) Whether to prompt the the user before downloading and loading study MultiAssayExperiment that is not currently building based on previous testing. Set to interactive() by default. In a non-interactive session, data download will be attempted; equivalent to ask = FALSE. The argument will also be used when a cache directory needs to be created when using downloadStudy.
cancer_study_file: character(1) indicates the on-disk location of the downloaded tarball
exdir: character(1) indicates the folder location to put the contents of the tarball (default tempdir(); see also ?untar)
filepath: character(1) indicates the folder location where the contents of the tarball are located (usually the same as exdir)
names.field: character() Possible column names for the column that will used to label ranges for data such as mutations or copy number (defaults: "Hugo_Symbol", "Entrez_Gene_Id", "Gene", and "Composite.Element.REF"). Values are cycled through and eliminated when no data present, or duplicates are found. Values in the corresponding column must be unique in each row.
cleanup: logical(1) whether to delete the untar-red contents from the exdir folder (default TRUE)

Value

downloadStudy - The file location of the data tarball
untarStudy - The directory location of the contents
loadStudy - A MultiAssayExperiment-class object

Details

When attempting to load a dataset using loadStudy, note that the cleanup argument is set to TRUE by default. Change the argument to FALSE if you would like to keep the untarred data in the exdir location. downloadStudy and untarStudy are not affected by this change. The tarball of the downloaded data is cached via BiocFileCache when use_cache is TRUE.

Examples

acc_file <- downloadStudy("acc_tcga")
#> Study file in cache: acc_tcga
acc_file
#>                                                               BFC4 
#> "/github/home/.cache/R/cBioPortalData/a1d7e2b6e07_acc_tcga.tar.gz" 

file_dir <- untarStudy(acc_file, tempdir())
file_dir
#> [1] "/tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga"

loadStudy(file_dir)
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_cna.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_cna_hg19.seg
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_linear_cna.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_methylation_hm450.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_mrna_seq_v2_rsem.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_mrna_seq_v2_rsem_zscores_ref_all_samples.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_mrna_seq_v2_rsem_zscores_ref_diploid_samples.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_mutations.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_mutsig.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_rppa.txt
#> Working on: /tmp/RtmpdbKWbS/a1d7e2b6e07_acc_tcga/acc_tcga/data_rppa_zscores.txt
#> Warning:  Multiple prefixes found, using keyword 'region' or taking first one
#> Warning:  Multiple prefixes found, using keyword 'region' or taking first one
#> A MultiAssayExperiment object of 10 listed
#>  experiments with user-defined names and respective classes.
#>  Containing an ExperimentList class object of length 10:
#>  [1] cna: SummarizedExperiment with 24776 rows and 90 columns
#>  [2] cna_hg19.seg: RaggedExperiment with 16080 rows and 90 columns
#>  [3] linear_cna: SummarizedExperiment with 24776 rows and 90 columns
#>  [4] methylation_hm450: SummarizedExperiment with 15754 rows and 80 columns
#>  [5] mrna_seq_v2_rsem: SummarizedExperiment with 20531 rows and 79 columns
#>  [6] mrna_seq_v2_rsem_zscores_ref_all_samples: SummarizedExperiment with 20531 rows and 79 columns
#>  [7] mrna_seq_v2_rsem_zscores_ref_diploid_samples: SummarizedExperiment with 20440 rows and 79 columns
#>  [8] mutations: RaggedExperiment with 20166 rows and 90 columns
#>  [9] rppa: SummarizedExperiment with 192 rows and 46 columns
#>  [10] rppa_zscores: SummarizedExperiment with 191 rows and 46 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

Usage

Arguments

Value

Details

See also

Examples