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--- a +++ b/R/simplify.R @@ -0,0 +1,871 @@ +# simplify TCGA data download workflow +## ------------------------------------ +# Typical Cohorts Structure + +# Given GBM as an example: <https://xenabrowser.net/datapages/?cohort=TCGA%20Glioblastoma%20(GBM)> +# Cohorts +# Copy Number +# gistic2 +# gistic2 thresholded +# Copy Number Segments +# After remove germline cnv +# Before remove germline cnv +# DNA Methylation +# Methylation27k +# Methylation450k +# Exon Expression RNASeq +# IlluminaHiSeq +# Gene Expression Array +# AffyU133a (always change) +# Gene Expression RNASeq +# IlluminaHiSeq +# IlluminaHiSeq pancan normalized +# IlluminaHiSeq percentile +# miRNA Mature Strand Expression RNASeq +# IlluminaHiseq +# PARADIGM Pathway Activity +# expression +# expression (array) + CNV +# expression + CNV +# exprssion (array) +# Phenotype +# Phenotypes +# Protein Expression RPPA +# RPPA +# RPPA (replicate-base normalization) +# Somatic Mutation (SNPs and small INDELs) +# broad +# ucsc automated +# Somatic non-silent mutation (gene-level) +# broad +# PANCAN AWG +# ucsc automated +# Transcription factor regulatory impact +# Agilent, by RABIT +# HiSeqV2, by RABIT +# U133A, by RABIT + +# compiler::setCompilerOptions(suppressAll = TRUE) +# suppress Binding Notes +# suppressBindingNotes <- function(variablesMentionedInNotes) { +# for(variable in variablesMentionedInNotes) { +# assign(variable, NULL, envir = .GlobalEnv) +# } +# } + +# suppressBindingNotes(c("XenaHostNames","XenaCohorts", "ProjectID", "DataType", "FileType")) + + +##' @title Get TCGA Common Data Sets by Project ID and Property +##' @description This is the most useful function for user to download common +##' TCGA datasets, it is similar to `getFirehoseData` function in `RTCGAToolbox` +##' package. +##' @details TCGA Common Data Sets are frequently used for biological analysis. +##' To make easier to achieve these data, this function provide really easy +##' options to choose datasets and behavior. All availble information about +##' datasets of TCGA can access vis `availTCGA()` and check with `showTCGA()`. +##' @author Shixiang Wang <w_shixiang@163.com> +##' @inheritParams downloadTCGA +##' @param clinical logical. if `TRUE`, download clinical information. Default is `TRUE`. +##' @param download logical. if `TRUE`, download data, otherwise return a result list include data +##' information. Default is `FALSE`. You can set this to `FALSE` if you want to check what you will download or +##' use other function provided by `UCSCXenaTools` to filter result datasets you want to download. +##' @param forceDownload logical. if `TRUE`, force to download files no matter if exist. Default is `FALSE`. +##' @param mRNASeq logical. if `TRUE`, download mRNASeq data. Default is `FALSE`. +##' @param mRNAArray logical. if `TRUE`, download mRNA microarray data. Default is `FALSE`. +##' @param mRNASeqType character vector. Can be one, two or three +##' in `c("normalized", "pancan normalized", "percentile")`. +##' @param miRNASeq logical. if `TRUE`, download miRNASeq data. Default is `FALSE`. +##' @param exonRNASeq logical. if `TRUE`, download exon RNASeq data. Default is `FALSE`. +##' @param RPPAArray logical. if `TRUE`, download RPPA data. Default is `FALSE`. +##' @param ReplicateBaseNormalization logical. if `TRUE`, download RPPA data by Replicate Base +##' Normalization (RBN). Default is `FALSE`. +##' @param Methylation logical. if `TRUE`, download DNA Methylation data. Default is `FALSE`. +##' @param MethylationType character vector. Can be one or two in `c("27K", "450K")`. +##' @param GeneMutation logical. if `TRUE`, download gene mutation data. Default is `FALSE`. +##' @param SomaticMutation logical. if `TRUE`, download somatic mutation data. Default is `FALSE`. +##' @param GisticCopyNumber logical. if `TRUE`, download Gistic2 Copy Number data. Default is `FALSE`. +##' @param Gistic2Threshold logical. if `TRUE`, download Threshold Gistic2 data. Default is `TRUE`. +##' @param CopyNumberSegment logical. if `TRUE`, download Copy Number Segment data. Default is `FALSE`. +##' @param RemoveGermlineCNV logical. if `TRUE`, download Copy Number Segment data which has removed +##' germline copy number variation. Default is `TRUE`. +##' @return if `download=TRUE`, return `data.frame` from `XenaDownload`, +##' otherwise return a list including `XenaHub` object and datasets information +##' @export +##' @examples +##' ###### get data, but not download +##' +##' # 1 choose project and data types you wanna download +##' getTCGAdata(project = "LUAD", mRNASeq = TRUE, mRNAArray = TRUE, +##' mRNASeqType = "normalized", miRNASeq = TRUE, exonRNASeq = TRUE, +##' RPPAArray = TRUE, Methylation = TRUE, MethylationType = "450K", +##' GeneMutation = TRUE, SomaticMutation = TRUE) +##' +##' # 2 only choose 'LUAD' and its clinical data +##' getTCGAdata(project = "LUAD") +##' \dontrun{ +##' ###### download datasets +##' +##' # 3 download clinical datasets of LUAD and LUSC +##' getTCGAdata(project = c("LUAD", "LUSC"), clinical = TRUE, download = TRUE) +##' +##' # 4 download clinical, RPPA and gene mutation datasets of LUAD and LUSC +##' # getTCGAdata(project = c("LUAD", "LUSC"), clinical = TRUE, RPPAArray = TRUE, GeneMutation = TRUE) +##' } +getTCGAdata <- function(project = NULL, + clinical = TRUE, + download = FALSE, + forceDownload = FALSE, + destdir = tempdir(), + mRNASeq = FALSE, + mRNAArray = FALSE, + mRNASeqType = "normalized", + miRNASeq = FALSE, + exonRNASeq = FALSE, + RPPAArray = FALSE, + ReplicateBaseNormalization = FALSE, + Methylation = FALSE, + MethylationType = c("27K", "450K"), + GeneMutation = FALSE, + SomaticMutation = FALSE, + GisticCopyNumber = FALSE, + Gistic2Threshold = TRUE, + CopyNumberSegment = FALSE, + RemoveGermlineCNV = TRUE, + ...) { + #----- check data type of input + stopifnot(!is.null(project)) + stopifnot(is.logical( + c( + clinical, + mRNASeq, + mRNAArray, + miRNASeq, + RPPAArray, + ReplicateBaseNormalization, + Methylation, + GeneMutation, + SomaticMutation, + GisticCopyNumber, + Gistic2Threshold, + CopyNumberSegment, + RemoveGermlineCNV, + download, + forceDownload + ) + )) + + projects <- c( + "LAML", + "ACC", + "CHOL", + "BLCA", + "BRCA", + "CESC", + "COADREAD", + "COAD", + "UCEC", + "ESCA", + "FPPP", + "GBM", + "HNSC", + "KICH", + "KIRC", + "KIRP", + "DLBC", + "LIHC", + "LGG", + "GBMLGG", + "LUAD", + "LUNG", + "LUSC", + "SKCM", + "MESO", + "UVM", + "OV", + "PANCAN", + "PAAD", + "PCPG", + "PRAD", + "READ", + "SARC", + "STAD", + "TGCT", + "THYM", + "THCA", + "UCS" + ) + + if (!all(project %in% projects)) { + message("Only following Project valid:") + print(project[project %in% projects]) + stop("Invaild Input!") + } + + tcga_all <- .decodeDataType(Target = "tcgaHub") + + # tcga_all %>% + # filter(ProjectID %in% project) %>% # select project + # filter() + + + res <- subset(tcga_all, ProjectID %in% project) + res %>% + filter( + DataType != "Transcription Factor Regulatory Impact", + DataType != "Signatures", + DataType != "PARADIGM Pathway Activity", + DataType != "iCluster" + ) -> res + + + if (clinical) { + quo_cli <- dplyr::quo((FileType == "Clinical Information")) + } else { + quo_cli <- dplyr::quo((FALSE)) + } + + if (mRNASeq) { + if (!all(mRNASeqType %in% c("normalized", "pancan normalized", "percentile"))) { + message("Available mRNASeqType values are:") + print(c("normalized", "pancan normalized", "percentile")) + stop("Not Vaild Input!") + } + + RNA <- c( + "IlluminaHiSeq RNASeqV2", + "IlluminaHiSeq RNASeqV2 pancan normalized", + "IlluminaHiSeq RNASeqV2 in percentile rank" + ) + names(RNA) <- c("normalized", "pancan normalized", "percentile") + RNA_select <- c(RNA[mRNASeqType], "Batch effects normalized") + + quo_RNA <- dplyr::quo(( + DataType == "Gene Expression RNASeq" & FileType %in% RNA_select + )) + } else { + quo_RNA <- dplyr::quo((FALSE)) + } + + if (mRNAArray) { + quo_RNAa <- dplyr::quo((DataType == "Gene Expression Array")) + } else { + quo_RNAa <- dplyr::quo((FALSE)) + } + + if (miRNASeq) { + miRNA_select <- c("IlluminaHiSeq RNASeq", "Batch effects normalized") + quo_miRNA <- dplyr::quo(( + DataType == "miRNA Mature Strand Expression RNASeq" & + FileType %in% miRNA_select + )) + } else { + quo_miRNA <- dplyr::quo((FALSE)) + } + + if (exonRNASeq) { + quo_exon <- dplyr::quo(( + DataType == "Exon Expression RNASeq" & + FileType == "IlluminaHiSeq RNASeqV2" + )) + } else { + quo_exon <- dplyr::quo((FALSE)) + } + # Have no miRNA Array? Need Check + # if(miRNAArray){ + # + # } + if (RPPAArray) { + if (ReplicateBaseNormalization) { + RPPA_select <- "RPPA normalized by RBN" + } else { + RPPA_select <- "RPPA" + } + quo_RPPA <- dplyr::quo(( + DataType == "Protein Expression RPPA" & + FileType %in% c(RPPA_select, "RPPA pancan normalized") + )) + } else { + quo_RPPA <- dplyr::quo((FALSE)) + } + + if (Methylation) { + if (!all(MethylationType %in% c("27K", "450K"))) { + message("Available MethylationType values are:") + print(c("27K", "450K")) + stop("Not Vaild Input!") + } + + Methy <- c("Methylation27K", "Methylation450K") + names(Methy) <- c("27K", "450K") + Methy_select <- Methy[MethylationType] + + quo_Methy <- dplyr::quo(( + DataType == "DNA Methylation" & FileType %in% Methy_select + )) + } else { + quo_Methy <- dplyr::quo((FALSE)) + } + + if (GeneMutation) { + quo_genMutation <- dplyr::quo(( + DataType == "Gene Somatic Non-silent Mutation" & + FileType %in% c("broad automated", "MC3 Public Version") + )) + } else { + quo_genMutation <- dplyr::quo((FALSE)) + } + + if (SomaticMutation) { + quo_somaticMutation <- dplyr::quo(( + DataType == "Somatic Mutation" & + FileType %in% c("broad automated", "MC3 Public Version") + )) + } else { + quo_somaticMutation <- dplyr::quo((FALSE)) + } + + if (GisticCopyNumber) { + if (Gistic2Threshold) { + gistic_select <- "Gistic2 thresholded" + } else { + gistic_select <- "Gistic2" + } + quo_gistic <- dplyr::quo(( + DataType == "Gene Level Copy Number" & FileType == gistic_select + )) + } else { + quo_gistic <- dplyr::quo((FALSE)) + } + + if (CopyNumberSegment) { + if (RemoveGermlineCNV) { + cns_select <- "After remove germline cnv" + } else { + cns_select <- "Before remove germline cnv" + } + quo_cns <- dplyr::quo(( + DataType == "Copy Number Segments" & FileType == cns_select + )) + } else { + quo_cns <- dplyr::quo((FALSE)) + } + + cond_select <- dplyr::quo( + !!quo_cli | + !!quo_RNA | + !!quo_RNAa | + !!quo_miRNA | + !!quo_exon | + !!quo_RPPA | + !!quo_Methy | + !!quo_genMutation | + !!quo_somaticMutation | !!quo_gistic | !!quo_cns + ) + res <- filter(res, !!cond_select) + + if (download) { + res %>% + XenaGenerate() %>% + XenaQuery() %>% + XenaDownload(destdir = destdir, force = forceDownload, ...) + } else { + xe <- res %>% XenaGenerate() + list(Xena = xe, DataInfo = res) + } +} + + + + +##' @title Easily Download TCGA Data by Several Options +##' @description TCGA is a very useful database and here we provide this function to +##' download TCGA (include TCGA Pancan) datasets in human-friendly way. Users who are not +##' familiar with R operation will benefit from this. +##' @details All availble information about datasets of TCGA can access vis `availTCGA()` and +##' check with `showTCGA()`. +##' @author Shixiang Wang <w_shixiang@163.com> +##' @param project default is `NULL`. Should be one or more of TCGA project id (character vector) provided by Xena. +##' See all available project id, please use `availTCGA("ProjectID")`. +##' @param data_type default is `NULL`. Should be a character vector specify data type. +##' See all available data types by `availTCGA("DataType")`. +##' @param file_type default is `NULL`. Should be a character vector specify file type. +##' See all available file types by `availTCGA("FileType")`. +##' @inheritParams XenaDownload +##' @return same as `XenaDownload()` function result. +##' @export +##' @examples +##' \dontrun{ +##' # download RNASeq data (use UVM as example) +##' downloadTCGA(project = "UVM", +##' data_type = "Gene Expression RNASeq", +##' file_type = "IlluminaHiSeq RNASeqV2") +##' } +##' @seealso [UCSCXenaTools::XenaQuery()], +##' [UCSCXenaTools::XenaFilter()], +##' [UCSCXenaTools::XenaDownload()], +##' [UCSCXenaTools::XenaPrepare()], +##' [UCSCXenaTools::availTCGA()], +##' [UCSCXenaTools::showTCGA()] + +downloadTCGA <- function(project = NULL, + data_type = NULL, + file_type = NULL, + destdir = tempdir(), + force = FALSE, + ...) { + stopifnot( + !is.null(project), + !is.null(data_type), + !is.null(file_type) + ) + tcga_all <- .decodeDataType(Target = "tcgaHub") + tcga_projects <- unique(tcga_all$ProjectID) + + # suppress binding notes + ProjectID <- DataType <- FileType <- NULL + + if (!all(project %in% tcga_projects)) { + message( + project, + " are not (all) valid, please select one or more of following valid project ID:" + ) + print(tcga_projects, quote = FALSE) + return(invisible(NULL)) + } + + res <- tcga_all %>% + filter( + ProjectID %in% project, + DataType %in% data_type, + FileType %in% file_type + ) + + if (nrow(res) == 0) { # nocov start + message("Find nothing about your input, please check it.") + message("availTCGA and showTCGA function may help you.") + return(invisible(NULL)) + } # nocov end + + res %>% + XenaGenerate() %>% + XenaQuery() %>% + XenaDownload(destdir = destdir, force = force, ...) +} + +##' @title Get or Check TCGA Available ProjectID, DataType and FileType +##' @param which a character of `c("All", "ProjectID", "DataType", "FileType")` +##' @author Shixiang Wang <w_shixiang@163.com> +##' @export +##' @examples +##' \donttest{ +##' availTCGA("all") +##' } +availTCGA <- function(which = c("all", "ProjectID", "DataType", "FileType")) { + which <- match.arg(which) + tcga_all <- .decodeDataType(Target = "tcgaHub") + tcga_projects <- unique(tcga_all$ProjectID) + tcga_datatype <- unique(tcga_all$DataType) + tcga_filetype <- unique(tcga_all$FileType) + + if (which == "all") { + message( + "Note not all projects have listed data types and file types, you can use showTCGA function to check if exist" + ) + return( + list( + ProjectID = tcga_projects, + DataType = tcga_datatype, + FileType = tcga_filetype + ) + ) + } + + if (which == "ProjectID") { + return(tcga_projects) + } + if (which == "DataType") { + return(tcga_datatype) + } + if (which == "FileType") { + return(tcga_filetype) + } +} + +##' @title Show TCGA data structure by Project ID or ALL +##' @description This can used to check if data type or file type exist in one or more projects by hand. +##' @param project a character vector. Can be "all" or one or more of TCGA Project IDs. +##' @return a `data.frame` including project data structure information. +##' @author Shixiang Wang <w_shixiang@163.com> +##' @export +##' @examples +##' \donttest{ +##' showTCGA("all") +##' } +##' @seealso [UCSCXenaTools::availTCGA()] +showTCGA <- function(project = "all") { + # suppress binding notes + ProjectID <- DataType <- FileType <- NULL + + tcga_all <- .decodeDataType(Target = "tcgaHub") + if (project == "all") { + # res = data.table::data.table(tcga_all) + # res = res[, .(ProjectID, DataType, FileType)] + res <- tcga_all %>% select(ProjectID, DataType, FileType) + } else { + res <- tcga_all %>% + filter(ProjectID %in% project) %>% + select(ProjectID, DataType, FileType) + # res = data.table::data.table(tcga_all) + # res = res[ProjectID %in% project, .(ProjectID, DataType, FileType)] + } + + if (nrow(res) == 0) { # nocov start + message("Something is wrong in your input, NULL will be returned, please check.") + return(NULL) + } # nocov end + return(res) +} + + + + +# Only works for TCGA +.decodeDataType <- function(XenaData = UCSCXenaTools::XenaData, + Target = "tcgaHub") { + # This TCGA include TCGA PANCAN dataset + if ("tcgaHub" %in% Target) { + Target <- c(Target, "pancanAtlasHub") + } + + # supress binding notes + XenaHostNames <- XenaCohorts <- NULL + + ob <- XenaData %>% filter(XenaHostNames %in% Target) + + if ("tcgaHub" %in% Target) { + # decode project id + ob %>% mutate(ProjectID = sub(".*\\((.*)\\)", "\\1", XenaCohorts)) -> ob + # decode DataType + ob %>% + mutate( + DataType = dplyr::case_when( + grepl("Gistic2_CopyNumber_Gistic2", XenaDatasets) ~ "Gene Level Copy Number", + grepl( + "PANCAN_Genome_Wide_SNP_6_whitelisted.gene.xena", + XenaDatasets + ) ~ "Gene Level Copy Number", + # pancan + grepl("SNP6", XenaDatasets) ~ "Copy Number Segments", + grepl( + "PANCAN_Genome_Wide_SNP_6_whitelisted.xena", + XenaDatasets + ) ~ "Copy Number Segments", + # pancan + grepl("HumanMethylation", XenaDatasets) ~ "DNA Methylation", + grepl("MethylMix", XenaDatasets) ~ "DNA Methylation", + grepl("HiSeq.*_exon", XenaDatasets) ~ "Exon Expression RNASeq", + grepl("GA_exon", XenaDatasets) ~ "Exon Expression RNASeq", + grepl("GAV2_exon", XenaDatasets) ~ "Exon Expression RNASeq", + grepl("AgilentG", XenaDatasets) ~ "Gene Expression Array", + grepl("HT_HG-U133A", XenaDatasets) ~ "Gene Expression Array", + grepl("GA$", XenaDatasets) & + !grepl("RABIT", XenaDatasets) ~ "Gene Expression RNASeq", + grepl("GAV2$", XenaDatasets) & + !grepl("RABIT", XenaDatasets) ~ "Gene Expression RNASeq", + grepl("HiSeq$", XenaDatasets) & + !grepl("RABIT", XenaDatasets) ~ "Gene Expression RNASeq", + grepl("HiSeqV2$", XenaDatasets) & + !grepl("RABIT", XenaDatasets) ~ "Gene Expression RNASeq", + grepl("HiSeqV2_PANCAN$", XenaDatasets) ~ "Gene Expression RNASeq", + grepl("HiSeqV2_percentile$", XenaDatasets) ~ "Gene Expression RNASeq", + grepl( + "EB\\+\\+AdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.xena", + XenaDatasets + ) ~ "Gene Expression RNASeq", + # pancan + grepl("miRNA", XenaDatasets) ~ "miRNA Mature Strand Expression RNASeq", + grepl( + "pancanMiRs_EBadjOnProtocolPlatformWithoutRepsWithUnCorrectMiRs", + XenaDatasets + ) ~ "miRNA Mature Strand Expression RNASeq", + # pancan + grepl("Pathway_Paradigm", XenaDatasets) ~ "PARADIGM Pathway Activity", + grepl("erge_merged_reals", XenaDatasets) ~ "PARADIGM Pathway Activity", + # pancan + grepl("clinicalMatrix", XenaDatasets) ~ "Phenotype", + grepl( + "Survival_SupplementalTable_S1_20171025_xena_sp", + XenaDatasets + ) ~ "Phenotype", + # pancan + grepl("Subtype_Immune_Model_Based.txt", XenaDatasets) ~ "Phenotype", + # pancan + grepl("TCGASubtype.20170308.tsv", XenaDatasets) ~ "Phenotype", + # pancan + grepl( + "TCGA_phenotype_denseDataOnlyDownload.tsv", + XenaDatasets + ) ~ "Phenotype", + # pancan + grepl("gene_expression_subtype", XenaDatasets) ~ "Phenotype", + # OV + grepl("RPPA", XenaDatasets) ~ "Protein Expression RPPA", + grepl("mutation_", XenaDatasets) & + !endsWith(XenaDatasets, "gene") ~ "Somatic Mutation", + grepl("mc3.v0.2.8.PUBLIC.xena", XenaDatasets) ~ "Somatic Mutation", + # pancan + grepl("mutation($|(.*_gene$))", XenaDatasets) ~ "Gene Somatic Non-silent Mutation", + grepl( + "mc3.v0.2.8.PUBLIC.nonsilentGene.xena", + XenaDatasets + ) ~ "Gene Somatic Non-silent Mutation", + # pancan + grepl("RABIT", XenaDatasets) ~ "Transcription Factor Regulatory Impact", + grepl("iCluster", XenaDatasets) ~ "iCluster", + grepl( + "Pancan12_GenePrograms_drugTargetCanon_in_Pancan33.tsv", + XenaDatasets + ) ~ "Signatures", + # pancan + grepl("TCGA.HRD_withSampleID.txt", XenaDatasets) ~ "Signatures", + # pancan + grepl( + "TCGA_pancancer_10852whitelistsamples_68ImmuneSigs.xena", + XenaDatasets + ) ~ "Signatures", + # pancan + grepl("StemnessScores_DNAmeth_20170210.tsv", XenaDatasets) ~ "Signatures", + # pancan + grepl( + "StemnessScores_RNAexp_20170127.2.tsv", + XenaDatasets + ) ~ "Signatures" # pancan + ) + ) -> ob + + # decode file type + ob %>% + mutate( + FileType = dplyr::case_when( + DataType == "Gene Level Copy Number" & + grepl("Gistic2_all_data_by_genes", XenaDatasets) ~ "Gistic2", + DataType == "Gene Level Copy Number" & + grepl("Gistic2_all_thresholded.by_genes", XenaDatasets) ~ "Gistic2 thresholded", + DataType == "Gene Level Copy Number" & + grepl( + "PANCAN_Genome_Wide_SNP_6_whitelisted.gene.xena", + XenaDatasets + ) ~ "Tumor copy number", + + + DataType == "Copy Number Segments" & + grepl("SNP6_genomicSegment", XenaDatasets) ~ "Before remove germline cnv", + DataType == "Copy Number Segments" & + grepl("SNP6_nocnv_genomicSegment", XenaDatasets) ~ "After remove germline cnv", + DataType == "Copy Number Segments" & + grepl( + "PANCAN_Genome_Wide_SNP_6_whitelisted.xena", + XenaDatasets + ) ~ "After remove germline cnv", + + + DataType == "DNA Methylation" & + grepl("HumanMethylation27", XenaDatasets) ~ "Methylation27K", + DataType == "DNA Methylation" & + grepl("HumanMethylation450", XenaDatasets) ~ "Methylation450K", + DataType == "DNA Methylation" & + grepl("oneoff_TCGA_LGG_MethylMix", XenaDatasets) ~ "MethylMix", + + + DataType == "Exon Expression RNASeq" & + grepl("GA_exon", XenaDatasets) ~ "IlluminaGA RNASeq", + DataType == "Exon Expression RNASeq" & + grepl("GAV2_exon", XenaDatasets) ~ "IlluminaGA RNASeqV2", + DataType == "Exon Expression RNASeq" & + grepl("HiSeq_exon", XenaDatasets) ~ "IlluminaHiSeq RNASeq", + DataType == "Exon Expression RNASeq" & + grepl("HiSeqV2_exon", XenaDatasets) ~ "IlluminaHiSeq RNASeqV2", + + + DataType == "Gene Expression Array" & + grepl("AgilentG4502A", XenaDatasets) ~ "Agilent 244K Microarray", + DataType == "Gene Expression Array" & + grepl("HT_HG-U133A", XenaDatasets) ~ "Affymetrix U133A Microarray", + + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "GA") ~ "IlluminaGA RNASeq", + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "GAV2") ~ "IlluminaGA RNASeqV2", + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "HiSeq") ~ "IlluminaHiSeq RNASeq", + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "HiSeqV2") ~ "IlluminaHiSeq RNASeqV2", + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "HiSeqV2_PANCAN") ~ "IlluminaHiSeq RNASeqV2 pancan normalized", + DataType == "Gene Expression RNASeq" & + endsWith(XenaDatasets, "HiSeqV2_percentile") ~ "IlluminaHiSeq RNASeqV2 in percentile rank", + DataType == "Gene Expression RNASeq" & + grepl("AdjustPANCAN_IlluminaHiSeq_RNASeqV2", XenaDatasets) ~ "Batch effects normalized", + + DataType == "miRNA Mature Strand Expression RNASeq" & + endsWith(XenaDatasets, "miRNA_GA_gene") ~ "IlluminaGA RNASeq", + DataType == "miRNA Mature Strand Expression RNASeq" & + endsWith(XenaDatasets, "miRNA_HiSeq_gene") ~ "IlluminaHiSeq RNASeq", + DataType == "miRNA Mature Strand Expression RNASeq" & + grepl( + "pancanMiRs_EBadjOnProtocolPlatformWithoutRepsWithU", + XenaDatasets + ) ~ "Batch effects normalized", + + + DataType == "PARADIGM Pathway Activity" & + grepl("merge_merged_reals", XenaDatasets) ~ "Platform-corrected PANCAN12 dataset", + DataType == "PARADIGM Pathway Activity" & + endsWith(XenaDatasets, "Pathway_Paradigm_mRNA") ~ "Use only Microarray", + DataType == "PARADIGM Pathway Activity" & + endsWith( + XenaDatasets, + "Pathway_Paradigm_mRNA_And_Copy_Number" + ) ~ "Use Microarray plus Copy Number", + DataType == "PARADIGM Pathway Activity" & + endsWith(XenaDatasets, "Pathway_Paradigm_RNASeq") ~ "Use only RNASeq", + DataType == "PARADIGM Pathway Activity" & + endsWith( + XenaDatasets, + "Pathway_Paradigm_RNASeq_And_Copy_Number" + ) ~ "Use RNASeq plus Copy Number", + + + DataType == "Phenotype" & + endsWith(XenaDatasets, "clinicalMatrix") ~ "Clinical Information", + DataType == "Phenotype" & + grepl( + "Survival_SupplementalTable_S1_20171025_xena_sp", + XenaDatasets + ) ~ "Clinical Information", + DataType == "Phenotype" & + grepl("gene_expression_subtype", XenaDatasets) ~ "Gene Expression Subtype", + DataType == "Phenotype" & + grepl("Subtype_Immune_Model_Based", XenaDatasets) ~ "Immune Model Based Subtype", + DataType == "Phenotype" & + grepl("TCGASubtype", XenaDatasets) ~ "TCGA Molecular Subtype", + DataType == "Phenotype" & + grepl( + "TCGA_phenotype_denseDataOnlyDownload", + XenaDatasets + ) ~ "TCGA Sample Type and Primary Disease", + + DataType == "Protein Expression RPPA" & + endsWith(XenaDatasets, "RPPA") ~ "RPPA", + DataType == "Protein Expression RPPA" & + endsWith(XenaDatasets, "RPPA_RBN") ~ "RPPA normalized by RBN", + DataType == "Protein Expression RPPA" & + grepl("TCGA-RPPA-pancan-clean", XenaDatasets) ~ "RPPA pancan normalized", + + + DataType == "Somatic Mutation" & + grepl("mc3.v0.2.8.PUBLIC.xena", XenaDatasets) ~ "MC3 Public Version", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_bcgsc") ~ "bcgsc automated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_bcm") ~ "bcm automated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_bcm_solid") ~ "bcm SOLiD", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_broad") ~ "broad automated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_curated_bcm") ~ "bcm curated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_curated_bcm_solid") ~ "bcm SOLiD curated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_curated_broad") ~ "broad curated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_curated_wustl") ~ "wustl curated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_ucsc_maf") ~ "ucsc automated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_wustl") ~ "wustl automated", + DataType == "Somatic Mutation" & + endsWith(XenaDatasets, "mutation_wustl_hiseq") ~ "wustl hiseq automated", + + DataType == "Gene Somatic Non-silent Mutation" & + grepl( + "mc3.v0.2.8.PUBLIC.nonsilentGene.xena", + XenaDatasets + ) ~ "MC3 Public Version", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation") ~ "PANCAN AWG analyzed", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_bcgsc_gene") ~ "bsgsc automated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_bcm_gene") ~ "bcm automated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_bcm_solid_gene") ~ "bcm SOLiD", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_broad_gene") ~ "broad automated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_curated_bcm_gene") ~ "bcm curated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_curated_bcm_solid_gene") ~ "bcm SOLiD curated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_curated_broad_gene") ~ "broad curated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_curated_wustl_gene") ~ "wustl curated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_ucsc_maf_gene") ~ "ucsc automated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_wustl_gene") ~ "wustl automated", + DataType == "Gene Somatic Non-silent Mutation" & + endsWith(XenaDatasets, "mutation_wustl_hiseq_gene") ~ "wustl hiseq automated", + + + DataType == "Transcription Factor Regulatory Impact" & + grepl("HiSeq.V2$", XenaDatasets) ~ "RABIT Use IlluminaHiSeq RNASeqV2", + DataType == "Transcription Factor Regulatory Impact" & + grepl("HiSeq$", XenaDatasets) ~ "RABIT Use IlluminaHiSeq RNASeq", + DataType == "Transcription Factor Regulatory Impact" & + grepl("GA.V2$", XenaDatasets) ~ "RABIT Use IlluminaGA RNASeqV2", + DataType == "Transcription Factor Regulatory Impact" & + grepl("GA$", XenaDatasets) ~ "RABIT Use IlluminaGA RNASeq", + DataType == "Transcription Factor Regulatory Impact" & + grepl("Agilent$", XenaDatasets) ~ "RABIT Use Agilent 244K Microarray", + DataType == "Transcription Factor Regulatory Impact" & + grepl("U133A$", XenaDatasets) ~ "RABIT Use Affymetrix U133A Microarray", + + DataType == "iCluster" & + grepl("TCGA_PanCan33_iCluster_k28_tumor", XenaDatasets) ~ "iCluster cluster assignments", + DataType == "iCluster" & + grepl("lat.vars.iCluster.redo.tumor", XenaDatasets) ~ "iCluster latent variables", + + DataType == "Signatures" & + grepl( + "Pancan12_GenePrograms_drugTargetCanon", + XenaDatasets + ) ~ "Pancan Gene Programs", + DataType == "Signatures" & + grepl("StemnessScores_DNAmeth_", XenaDatasets) ~ "DNA methylation based StemnessScore", + DataType == "Signatures" & + grepl("StemnessScores_RNAexp", XenaDatasets) ~ "RNA based StemnessScore", + DataType == "Signatures" & + grepl( + "TCGA_pancancer_10852whitelistsamples_68ImmuneSigs", + XenaDatasets + ) ~ "Immune Signature Scores", + DataType == "Signatures" & + grepl("TCGA.HRD_withSampleID.txt", XenaDatasets) ~ "Genome-wide DNA Damage Footprint HRD Score" + ) + ) -> ob_tcga + } + ob_tcga +} + + + +# grep unique pattern +# ob1 = sub("TCGA.*/(.*)", "\\1", ob$XenaDatasets) %>% table() %>% names() -> uniqueDatasets +# ob1 = tibble(XenaDatasets = uniqueDatasets) +# grep("gene_expression_subtype", ob$XenaDatasets, value = TRUE) + + +utils::globalVariables(c("DataType", "FileType", "ProjectID"))