GDCprepare {TCGAbiolinks} | R Documentation

## Prepare GDC data

### Description

Reads the data downloaded and prepare it into an R object

### Usage

    GDCprepare(query, save = FALSE, save.filename, directory = "GDCdata",
      summarizedExperiment = TRUE, remove.files.prepared = FALSE,
      add.gistic2.mut = NULL, mut.pipeline = "mutect2",
      mutant_variant_classification = c("Frame_Shift_Del", "Frame_Shift_Ins",
      "Missense_Mutation", "Nonsense_Mutation", "Splice_Site", "In_Frame_Del",
      "In_Frame_Ins", "Translation_Start_Site", "Nonstop_Mutation"))

### Arguments

`query` | A query for GDCquery function
`save` | Save result as RData object?
`save.filename` | Name of the file to be save if empty an automatic will be created
`directory` | Directory/Folder where the data was downloaded. Default: GDCdata
`summarizedExperiment` | Create a summarizedExperiment? Default TRUE (if possible)
`remove.files.prepared` | Remove the files read? Default: FALSE This argument will be considered only if save argument is set to true
`add.gistic2.mut` | If a list of genes (gene symbol) is given, columns with gistic2 results from GDAC firehose (hg19) and a column indicating if there is or not mutation in that gene (hg38) (TRUE or FALSE - use the MAF file for more information) will be added to the sample matrix in the summarized Experiment object.
`mut.pipeline` | If add.gistic2.mut is not NULL this field will be taken in consideration. Four separate variant calling pipelines are implemented for GDC data harmonization. Options: muse, varscan2, somaticsniper, MuTect2. For more information: https://gdc-docs.nci.nih.gov/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline/
`mutant_variant_classification` | List of mutant_variant_classification that will be consider a sample mutant or not. Default: "Frame_Shift_Del", "Frame_Shift_Ins", "Missense_Mutation", "Nonsense_Mutation", "Splice_Site", "In_Frame_Del", "In_Frame_Ins", "Translation_Start_Site", "Nonstop_Mutation"

### Value

A summarizedExperiment or a data.frame

### Examples

    query <- GDCquery(project = "TCGA-KIRP",
                      data.category = "Simple Nucleotide Variation",
                      data.type = "Masked Somatic Mutation",
                      workflow.type = "MuSE Variant Aggregation and Masking")
    GDCdownload(query, method = "api", directory = "maf")
    maf <- GDCprepare(query, directory = "maf")

    ## Not run:
    query <- GDCquery(project = "TCGA-ACC",
                       data.category =  "Copy number variation",
                       legacy = TRUE,
                       file.type = "hg19.seg",
                       barcode = c("TCGA-OR-A5LR-01A-11D-A29H-01", "TCGA-OR-A5LJ-10A-01D-A29K-01"))
    # data will be saved in  GDCdata/TCGA-ACC/legacy/Copy_number_variation/Copy_number_segmentation
    GDCdownload(query, method = "api")
    acc.cnv <- GDCprepare(query)
     query <- GDCquery(project = "TCGA-GBM",
                       legacy = TRUE,
                       data.category = "Gene expression",
                       data.type = "Gene expression quantification",
                       platform = "Illumina HiSeq",
                       file.type = "normalized_results",
                       experimental.strategy = "RNA-Seq")
     GDCdownload(query, method = "api")
     data <- GDCprepare(query,add.gistic2.mut = c("PTEN","FOXJ1"))

    ## End(Not run)

[Package TCGAbiolinks version 2.8.4 Index]