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Module_A.R
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# =============================================================================
# TCGA-Assembler version 2
#
# Copyright (C) <2017> <Yitan Zhu>
# This file is part of TCGA-Assembler.
#
# TCGA-Assembler is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# TCGA-Assembler is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with TCGA-Assembler. If not, see <http://www.gnu.org/licenses/>.
# =============================================================================
# =============================================================================
# TCGA-Assembler Version 2 Module A
# =============================================================================
# =============================================================================
# variable prefix example
# =============================================================================
# s : string
# n : number
# v : vector
# d : data.frame
# m : matrix
# l : list
# lv : list of vector
# ld : list of data.frame
# =============================================================================
# internal functions, NOT used directly by user
# =============================================================================
#' Get fields names of GDC entities
#'
#' @param arch String of archive type: "legacy" or "".
#' @param endp String of endpoint: "files".
#' @return Character vector of all available field names.
#' @examples
#' fieldsList <- FieldsList("legacy")
#' fieldsList <- FieldsList("")
FieldsList <- function(arch = "legacy",
endp = "files") {
library(rjson)
url <- paste("https://gdc-api.nci.nih.gov/",
arch,
ifelse(arch == "", "", "/"),
endp,
"/_mapping",
sep = "")
opt <- "--silent --show-error"
arg <- paste(opt, url)
jsn <- paste(system2("curl", arg, stdout = T), collapse = "")
return(fromJSON(jsn)$fields)
}
#' Define the default fields used in metadata file
#'
#' @return Character vector of selected fields names for metadata.
FieldsMeta <- function() {
return(c(# "access",
"archive.file_name",
# "cases.case_id",
"cases.project.project_id",
"cases.samples.portions.analytes.aliquots.submitter_id", # 1st
# "cases.samples.portions.analytes.submitter_id",
"cases.samples.portions.submitter_id", # 2nd
"cases.samples.sample_type",
"cases.samples.sample_type_id", # sprintf("%02d", c(seq(14), 20, 40, 50, 60, 61))
"data_category",
"data_type",
"experimental_strategy",
"file_id",
"file_name",
"file_size",
# "md5sum",
"platform",
"updated_datetime"))
}
#' Get count of GDC entities in /archive/endpoint
#'
#' @param arch String of archive type: "legacy" or "".
#' @param endp String of endpoint: "files".
#' @return Count of entities in specified archive & endpoint.
#' @examples
#' entityCount <- EntityCount("legacy")
#' entityCount <- EntityCount("")
EntityCount <- function(arch = "legacy",
endp = "files") {
library(rjson)
url <- paste("https://gdc-api.nci.nih.gov/",
arch,
ifelse(arch == "", "", "/"),
endp,
sep = "")
opt <- "--silent --show-error"
arg <- paste(opt, url)
jsn <- paste(system2("curl", arg, stdout = T), collapse = "")
# stopifnot(length(fromJSON(jsn)$warnings) == 0)
return(fromJSON(jsn)$data$pagination$total)
}
#' Get a string of current time (YYYYMMDDhhmmss)
#'
#' @return String of current time (YYYYMMDDhhmmss).
#' @examples
#' TimeNow()
TimeNow <- function() {
return(gsub("[- :]", "", as.character(Sys.time())))
}
#' Get index of the entity with newest archive file version
#'
#' @param archiveNames Character vector of "archive.file_name". All of
#' these entities have same "file_name".
#' @return Index of the newest one.
#' @examples
#' v <- c("mdanderson.org_BRCA.MDA_RPPA_Core.Level_3.114.1.0.tar.gz",
#' "mdanderson.org_BRCA.MDA_RPPA_Core.Level_3.2.1.0.tar.gz",
#' "mdanderson.org_BRCA.MDA_RPPA_Core.Level_3.10.1.0.tar.gz")
#' n <- ArchiveNewest(v)
ArchiveNewest <- function(archiveNames) {
m <- sapply(strsplit(archiveNames, split = "\\."),
function(x){rev(x)[5 : 3]})
mode(m) <- "numeric" # OR class(m) <- "numeric"
vOrder <- do.call(order, lapply(seq(nrow(m)), function(x){m[x, ]}))
return(vOrder[length(vOrder)])
}
#' Get vector of bool indicate the one with newest archive file version or not
#' in one group
#'
#' @param archiveNames Character vector of "archive.file_name". All of
#' these entities have same "file_name".
#' @return Bool vector to indicate the newest one in one group
ArchiveNewestInGroup <- function(archiveNames) {
b <- seq(length(archiveNames)) == ArchiveNewest(archiveNames)
return(ifelse(b, T, F))
}
#' Get vector of bool indicate the one with newest archive file version or not
#' in every group
#'
#' @param archiveNames Character vector of "archive.file_name", could be
#' split into groups, each group with a unique "file_name".
#' @param splitFactor Character vector of "file_name" (sorted).
#' @return Bool vector to indicate the newest one in every group.
ArchiveNewestInGroups <- function(archiveNames,
splitFactor) {
stopifnot(all(splitFactor == splitFactor[order(splitFactor)])) # splitFactor should be sorted before split
return(unlist(lapply(split(archiveNames, splitFactor),
ArchiveNewestInGroup)))
}
#' Choose columns from a file
#'
#' @param fileName String of filename.
#' @param fileId String of fileId with same length of fileName.
#' @param colNames Character vector of colname, specify the columns choosed.
#' @param sortBy Name one column which acts as the rownames.
#' @param skipLines Number of lines skipped in \code{read.csv}.
#' @param naStrings String indicating the \code{NA} in \code{read.csv}.
#' @return A \code{data.frame} with specified columns from one file.
ColumnsFromFile <- function(fileName,
fileId,
colNames,
sortBy = "",
skipLines = 0,
naStrings) {
d <- read.csv(fileName,
sep = "\t",
row.names = NULL,
as.is = T,
skip = skipLines,
na.strings = naStrings)
if (sortBy != "") {
if (length(d[, sortBy]) != length(unique(d[, sortBy]))) { # probe duplicated, check same value for each probe group
stopifnot(all(tapply(Reduce(paste, d[, colNames]), d[, sortBy],
function(x){length(unique(x)) == 1})))
d <- d[!duplicated(d[, sortBy]), ]
}
stopifnot(length(d[, sortBy]) == length(unique(d[, sortBy])))
rownames(d) <- d[, sortBy]
d <- d[order(d[, sortBy]), colNames]
} else {
d <- cbind("fileId" = rep(fileId, dim(d)[1]), d[, colNames])
}
return(d)
}
#' Choose columns from each file of filenames
#'
#' @param fileName String of filename, named with file_id.
#' @param colNames Character vector of colname, specify the columns choosed.
#' @param sortBy Name one column which acts as the rownames.
#' @param skipLines Number of lines skipped in \code{read.csv}.
#' @param naStrings String indicating the \code{NA} in \code{read.csv}.
#' @return List of \code{data.frame} with specified columns from each file.
ColumnsFromFiles <- function(fileNameById,
colNames,
sortBy = "",
skipLines = 0,
naStrings = "NA") {
l <- lapply(names(fileNameById),
function(x){
ColumnsFromFile(fileNameById[x],
x,
colNames,
sortBy,
skipLines,
naStrings)
})
names(l) <- names(fileNameById)
return(l)
}
#' Strip characters at left or right end of each string in a vector
#'
#' @param vUnstripped Character vector of unstripped strings.
#' @param stripNum Number of characters need to be stripped.
#' @param stripEnd Sting indicating the terminal: "right" or "left".
#' @return Character vector of stripped strings.
StripEnd <- function(vUnstripped,
stripNum,
stripEnd = "right") {
if (stripNum == 0) {
vStripped <- vUnstripped
} else {
if (stripEnd %in% c("r", "right")) {
vStripped <- sapply(strsplit(vUnstripped, split = ""),
function(x){
paste(x[-((length(x) - stripNum + 1) : length(x))],
collapse = "")
})
} else if (stripEnd %in% c("l", "left")) {
vStripped <- sapply(strsplit(vUnstripped, split = ""),
function(x){
paste(x[-(1 : stripNum)], collapse = "")
})
} else {
print("stripEnd should be one of 'right', 'r', 'l' or 'left'")
}
}
return(vStripped)
}
#' Make a vector of values named with probes
#'
#' @param dProbeValue A \code{data.frame}, usually read from filename.
#' @param colProbe String of column name of probe, used as name.
#' @param colValue String of column name of value.
#' @param stripNum Number of characters need to be stripped from "probe".
#' @param stripEnd Sting indicating the terminal: "right" or "left".
#' @return Named vector.
ProbeValue <- function(dProbeValue,
colProbe,
colValue,
stripNum = 0,
stripEnd = "right") {
v <- dProbeValue[, colValue]
names(v) <- StripEnd(dProbeValue[, colProbe], stripNum, stripEnd)
return(v)
}
#' Cut the "*\\.1\\.*" columns and rows with \code{NA} only
#'
#' @param metaData A \code{data.frame} read from metadata file.
#' @param colPattern String of regular expression pattern to filter colname.
#' @return A \code{data.frame} after cutting.
MetaCut <- function(metaData,
colPattern = "\\.1\\.") {
colIdx <- grep(colPattern, colnames(metaData))
rowIdx <- sapply(seq(dim(metaData)[1]),
function(x){
ifelse(all(is.na(metaData[x, colIdx])), T, F)
})
metaCut <- metaData[rowIdx, seq(dim(metaData)[2])[-colIdx]]
return(metaCut)
}
#' Define the filters with specified assay platform
#'
#' @param sAssay String of assay platform.
#' @return List of filter.
#' @example
#' filter <- Filter("methylation_450")
Filter <- function(sAssay) {
filter <- list()
vAssay <- c(# Copy number segmentation
"cna_cnv.hg18",
"cna_cnv.hg19",
"cna_nocnv.hg18",
"cna_nocnv.hg19",
# Exon junction quantification
"exonJunction_RNAseq",
"exonJunction_TotalRNAseq",
# Exon quantification
"exon_RNAseq",
"exon_TotalRNAseq",
# Gene expression quantification
"gene_Array",
"gene.normalized_RNAseq",
"gene_RNAseq",
"gene.normalized_TotalRNAseq",
"gene_TotalRNAseq",
# Isoform expression quantification
"isoform.normalized_RNAseq",
"isoform_RNAseq",
"isoform.normalized_TotalRNAseq",
"isoform_TotalRNAseq",
# Methylation beta value
"methylation_27",
"methylation_450",
# miRNA gene quantification
"mir_GA.hg18",
"mir_GA.hg19",
"mir_GA.hg19.mirbase20",
# miRNA gene quantification
"mir_HiSeq.hg18",
"mir_HiSeq.hg19",
"mir_HiSeq.hg19.mirbase20",
# miRNA isoform quantification
"mirIsoform_GA.hg18",
"mirIsoform_GA.hg19",
"mirIsoform_GA.hg19.mirbase20",
# miRNA isoform quantification
"mirIsoform_HiSeq.hg18",
"mirIsoform_HiSeq.hg19",
"mirIsoform_HiSeq.hg19.mirbase20",
# Protein expression quantification
"protein_RPPA",
# Simple somatic mutation
"somaticMutation_DNAseq",
# CPTAC
"glycoproteome_iTRAQ",
"phosphoproteome_iTRAQ",
"proteome_iTRAQ")
if (!sAssay %in% vAssay) { # assayPlatform = sAssay
print(paste(c("assayPlatform should be one of:", vAssay), collapse = " "))
} else if (sAssay == "cna_cnv.hg18") {
filter$data_category <- c("Copy number variation")
filter$data_type <- c("Copy number segmentation")
filter$experimental_strategy <- "Genotyping array"
filter$platform <- "Affymetrix SNP Array 6.0"
filter$file_name <- "\\.hg18\\.seg\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "cna_cnv.hg19") {
filter$data_category <- c("Copy number variation")
filter$data_type <- c("Copy number segmentation")
filter$experimental_strategy <- "Genotyping array"
filter$platform <- "Affymetrix SNP Array 6.0"
filter$file_name <- "\\.hg19\\.seg\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "cna_nocnv.hg18") {
filter$data_category <- c("Copy number variation")
filter$data_type <- c("Copy number segmentation")
filter$experimental_strategy <- "Genotyping array"
filter$platform <- "Affymetrix SNP Array 6.0"
filter$file_name <- "\\.nocnv_hg18\\.seg\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "cna_nocnv.hg19") {
filter$data_category <- c("Copy number variation")
filter$data_type <- c("Copy number segmentation")
filter$experimental_strategy <- "Genotyping array"
filter$platform <- "Affymetrix SNP Array 6.0"
filter$file_name <- "\\.nocnv_hg19\\.seg\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "exon_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Exon quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.bt\\.exon_quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "exon_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Exon quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.bt\\.exon_quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "exonJunction_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Exon junction quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.junction_quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "exonJunction_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Exon junction quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.junction_quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "gene_Array") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Gene expression quantification"
filter$experimental_strategy <- "Gene expression array"
filter$platform <- "AgilentG4502A_07_3"
filter$file_name <- "\\.txt_lmean\\.out\\.logratio\\.gene\\.tcga_level3\\.data\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "gene.normalized_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Gene expression quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.genes\\.normalized_results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "gene_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Gene expression quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.genes\\.results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "gene.normalized_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Gene expression quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.genes\\.normalized_results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "gene_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Gene expression quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.genes\\.results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "isoform.normalized_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Isoform expression quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.isoforms\\.normalized_results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "isoform_RNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Isoform expression quantification"
filter$experimental_strategy <- "RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.isoforms\\.results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "isoform.normalized_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Isoform expression quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.isoforms\\.normalized_results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "isoform_TotalRNAseq") {
filter$data_category <- c("Gene expression")
filter$data_type <- "Isoform expression quantification"
filter$experimental_strategy <- "Total RNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "\\.rsem\\.isoforms\\.results"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_GA.hg18") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_GA.hg19") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_GA.hg19.mirbase20") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirbase20\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_HiSeq.hg18") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_HiSeq.hg19") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mir_HiSeq.hg19.mirbase20") {
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA gene quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirbase20\\.mirna\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_GA.hg18") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_GA.hg19") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.hg19\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_GA.hg19.mirbase20") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina GA"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirbase20\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_HiSeq.hg18") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_HiSeq.hg19") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.hg19\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "mirIsoform_HiSeq.hg19.mirbase20") { # rows different
filter$data_category <- c("Gene expression")
filter$data_type <- "miRNA isoform quantification"
filter$experimental_strategy <- "miRNA-Seq"
filter$platform <- "Illumina HiSeq"
filter$file_name <- "^[^\\.]*\\.hg19\\.mirbase20\\.isoform\\.quantification\\.txt"
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "methylation_27") {
filter$data_category <- "DNA methylation"
filter$data_type <- "Methylation beta value"
filter$experimental_strategy <- "Methylation array"
filter$platform <- "Illumina Human Methylation 27"
filter$file_name <- "jhu-usc\\.edu_.*\\.HumanMethylation27\\."
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "methylation_450") {
filter$data_category <- "DNA methylation"
filter$data_type <- "Methylation beta value"
filter$experimental_strategy <- "Methylation array"
filter$platform <- "Illumina Human Methylation 450"
filter$file_name <- "jhu-usc\\.edu_.*\\.HumanMethylation450\\."
filter$submitter_id <- "cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id"
} else if (sAssay == "protein_RPPA") { # differnt "archive.file_name"
filter$data_category <- "Protein expression"
filter$data_type <- "Protein expression quantification"
filter$experimental_strategy <- "Protein expression array"
filter$platform <- "MDA_RPPA_Core"
filter$file_name <-
"mdanderson\\.org_.*\\.MDA_RPPA_Core\\.protein_expression\\.Level_3\\."
filter$submitter_id <- "cases.0.samples.0.portions.0.submitter_id"
} else if (sAssay == "somaticMutation_DNAseq") {
filter$data_category <- "Simple nucleotide variation"
filter$data_type <- "Simple somatic mutation"
filter$experimental_strategy <- "DNA-Seq"
filter$platform <- c("Illumina GA", "Illumina HiSeq", "Mixed platforms")
filter$file_name <- "\\.somatic\\.maf"
filter$submitter_id <- c("cases.0.samples.0.portions.0.submitter_id", # both exist
"cases.0.samples.0.portions.0.analytes.0.aliquots.0.submitter_id")
} else if (sAssay == "glycoproteome_iTRAQ") { # from CTPAC not GDC
filter$data_category <- NA
filter$data_type <- NA
filter$experimental_strategy <- NA
filter$platform <- "glycoproteome_iTRAQ"
filter$file_name <- "_Glycoproteome\\.glycosite\\.itraq\\.tsv"
filter$submitter_id <- NA
} else if (sAssay == "phosphoproteome_iTRAQ") { # from CTPAC not GDC
filter$data_category <- NA
filter$data_type <- NA
filter$experimental_strategy <- NA
filter$platform <- "phosphoproteome_iTRAQ"
filter$file_name <- "_Phosphoproteome\\.phosphosite\\.itraq\\.tsv"
filter$submitter_id <- NA
} else if (sAssay == "proteome_iTRAQ") { # from CTPAC not GDC
filter$data_category <- NA
filter$data_type <- NA
filter$experimental_strategy <- NA
filter$platform <- "proteome_iTRAQ"
filter$file_name <- "_Proteome.(itraq|spectral_counts)\\.tsv"
filter$submitter_id <- NA
}
return(filter)
}
#' Get metadata of biospecimen & clinical data files with defined filter
#'
#' @param tmpDir String of directory for temporary files.
#' @param arch String of archive type: "legacy" or "".
#' @param fieldsMeta Character vector of colnames in metadata.
#' @param entityCount Number of entity (row) in the metadata: "-1" means all.
#' @param endp String of endpoint: "files".
#' @return A \code{data.frame} of metadata.
#' @example
#' metadata <- MetaDataClin(tmpDir = ".")
MetaDataClin <- function(tmpDir = ".",
arch = "legacy",
fieldsMeta = "",
entityCount = (-1),
endp = "files") {
library(rjson)
if (entityCount == (-1)) {
entityCount <- EntityCount(arch, endp)
}
if (fieldsMeta == "") {
fieldsMeta <- FieldsMeta()
} else {
fieldsList <- FieldsList(arch, endp)
print("fields names: checking ...")
stopifnot(all(fieldsMeta %in% fieldsList))
print("fields names: checking done!")
}
print("metadata file: preparing ...")
out <- paste(tmpDir, "/tmp_metadata_", endp, ".tsv", sep = "")
url <- paste('"https://gdc-api.nci.nih.gov/', arch,
ifelse(arch == '', '', '/'), endp, '"',
sep = '')
opt <- paste("-o ", out,
" --silent --show-error --request POST",
" --header Content-Type:application/json --data @",
tmpDir, "/tmp_metadata.json",
sep = "")
arg <- paste(opt, url)
filter2 <- list()
filter2$access <- list(op = "=",
content = list(field = "access", value = "open"))
filter2$data_format <- list(op = "in",
content = list(field = "data_format",
value = "Biotab"))
filterAll <- list(op = "and",
content = list(filter2$access,
filter2$data_format))
payload <- list(filters = filterAll,
format = "TSV",
sort = "file_id",
from = 1,
size = entityCount,
fields = paste(fieldsMeta, collapse = ","))
cat(toJSON(payload), file = paste(tmpDir, "/tmp_metadata.json", sep = ""))
stdOut <- system2("curl", arg, stdout = T)
if (!is.null(attr(stdOut, "status"))) {
print("error (download): check the proxy")
}
stopifnot(is.null(attr(stdOut, "status")))
if ("data" %in% dir()) {file.remove("data")}
metaData <- tryCatch(read.csv(out,
sep = "\t",
row.names = NULL,
as.is = T,
na.strings = ""),
error = function(e){print(e$message); return(NULL)})
if (!is.null(metaData)) { # > 0 lines available in input
if (nrow(metaData) == 0) {
metaData <- NULL
} else {
write.table(metaData,
file = paste(tmpDir,
"/tmp_metadata_clinical__",
arch,
"__",
endp,
".tsv",
sep = ""),
quote = F,
sep = "\t",
col.names = NA,
row.names = T)
}
}
print("metadata file: preparing done!")
return(metaData)
}
#' Get metadata of somatic mutation data files with defined filter
#'
#' @param vCancer String of cancer type.
#' @param sAssay String of assay platform, used in \code{Filter}.
#' @param sampleTypeId Character vector of sample_type_id: "01", ..., "14", etc.
#' @param tmpDir String of directory for temporary files.
#' @param arch String of archive type: "legacy" or "".
#' @param fieldsMeta Character vector of colnames in metadata.
#' @param entityCount Number of entity (row) in the metadata: "-1" means all.
#' @param endp String of endpoint: "files".
#' @return A \code{data.frame} of metadata.
MetaDataSoma <- function(vCancer = "BRCA",
sAssay,
sampleTypeId = sprintf("%02d", c(seq(14), 20, 40, 50, 60, 61)),
tmpDir = ".",
arch = "legacy",
fieldsMeta = "",
entityCount = (-1),
endp = "files") {
library(rjson)
if (entityCount == (-1)) {
entityCount <- EntityCount(arch, endp)
}
if (fieldsMeta == "") {
fieldsMeta <- FieldsMeta()
} else {
fieldsList <- FieldsList(arch, endp)
print("fields names: checking ...")
stopifnot(all(fieldsMeta %in% fieldsList))
print("fields names: checking done!")
}
filter <- Filter(sAssay)
print("metadata file: preparing ...")
out <- paste(tmpDir, "/tmp_metadata_", endp, ".tsv", sep = "")
url <- paste('"https://gdc-api.nci.nih.gov/', arch,
ifelse(arch == '', '', '/'), endp, '"',
sep = '')
opt <- paste("-o ", out, " --silent --show-error --request POST ",
"--header Content-Type:application/json --data @",
tmpDir, "/tmp_metadata.json", sep = "")
arg <- paste(opt, url)
filter2 <- list()
filter2$access <- list(op = "=" ,
content = list(field = "access",
value = "open"))
filter2$data_format <- list(op = "in",
content = list(field = "data_format",
value = "MAF"))
filter2$project_id <- list(op = "in",
content = list(field = "cases.project.project_id",
value = paste("TCGA", vCancer,
sep = "-")))
filter2$data_category <- list(op = "in",
content = list(field = "data_category",
value = filter$data_category))
filter2$data_type <- list(op = "in",
content = list(field = "data_type",
value = filter$data_type))
filter2$experimental_strategy <- list(op = "in",
content = list(field = "experimental_strategy",
value = filter$experimental_strategy))
filter2$platform <- list(op = "in",
content = list(field = "platform",
value = filter$platform))
filterAll <- list(op = "and",
content = list(filter2$access,
filter2$data_format,
filter2$project_id,
filter2$data_category,
filter2$data_type,
filter2$experimental_strategy,
filter2$platform))
payload <- list(filters = filterAll,
format = "TSV",
sort = "file_id",
from = 1,
size = entityCount,
fields = paste(fieldsMeta, collapse = ","))
cat(toJSON(payload), file = paste(tmpDir, "/tmp_metadata.json", sep = ""))
stdOut <- system2("curl", arg, stdout = T)
if (!is.null(attr(stdOut, "status"))) {
print("error (download): check the proxy")
}
stopifnot(is.null(attr(stdOut, "status")))
if ("data" %in% dir()) {file.remove("data")}
metaData <- tryCatch(read.csv(out,
sep = "\t",
row.names = NULL,
as.is = T,
na.strings = ""),
error = function(e){print(e$message); return(NULL)})
if (!is.null(metaData)) { # > 0 lines available in input
colNames <- c("archive.file_name",
"cases.0.project.project_id",
"data_category",
"data_type",
"experimental_strategy",
"file_id",
"file_name",
"file_size",
"platform",
"updated_datetime")
metaData <- metaData[, colNames]
rownames(metaData) <- metaData[, "file_id"]
write.table(metaData,
file = paste(tmpDir,
"/tmp_metadata_byType__",
arch,
"__",
endp,
"__",
paste(vCancer, collapse = "_"),
"__",
sAssay,
".tsv",
sep = ""),
quote = F,
sep = "\t",
col.names = NA,
row.names = T)
}
print("metadata file: preparing done!")
return(metaData)
}
#' Get metadata of spefified assay platform files with defined filter
#'
#' @param vCancer String of cancer type.
#' @param sAssay String of assay platform, used in \code{Filter}.
#' @param sampleTypeId Character vector of sample_type_id: "01", ..., "14", etc.
#' @param tmpDir String of directory for temporary files.
#' @param arch String of archive type: "legacy" or "".
#' @param fieldsMeta Character vector of colnames in metadata.
#' @param entityCount Number of entity (row) in the metadata: "-1" means all.
#' @param endp String of endpoint: "files".
#' @return A \code{data.frame} of metadata.
#' @example
#' metaData <- function(vCancer = "BRCA",
#' sAssay = "gene_RNAseq",
#' sampleTypeId = sprintf("%02d", c(seq(14), 20, 40, 50, 60, 61)),
#' tmpDir = ".",
#' arch = "legacy",
#' fieldsMeta = "",
#' entityCount = (-1),
#' endp = "files")
MetaData <- function(vCancer = "BRCA",
sAssay,
sampleTypeId = sprintf("%02d", c(seq(14), 20, 40, 50, 60, 61)),
tmpDir = ".",
arch = "legacy",
fieldsMeta = "",
entityCount = (-1),
endp = "files") {
library(rjson)
if (entityCount == (-1)) {
entityCount <- EntityCount(arch, endp)
}
if (fieldsMeta == "") {
fieldsMeta <- FieldsMeta()
} else {
fieldsList <- FieldsList(arch, endp)
print("fields names: checking ...")
stopifnot(all(fieldsMeta %in% fieldsList))
print("fields names: checking done!")
}
filter <- Filter(sAssay)
print("metadata file: preparing ...")
out <- paste(tmpDir, "/tmp_metadata_", endp, ".tsv", sep = "")
url <- paste('"https://gdc-api.nci.nih.gov/', arch,
ifelse(arch == '', '', '/'), endp, '"',
sep = '')
opt <- paste("-o ", out,
" --silent --show-error --request POST",
" --header Content-Type:application/json --data @",
tmpDir, "/tmp_metadata.json",
sep = "")
arg <- paste(opt, url)
filter2 <- list()
filter2$access <- list(op = "=" ,
content = list(field = "access",
value = "open"))
filter2$data_format <- list(op = "in",
content = list(field = "data_format",
value = "TXT"))
filter2$project_id <- list(op = "in",
content = list(field = "cases.project.project_id",
value = paste("TCGA", vCancer,
sep = "-")))
filter2$data_category <- list(op = "in",
content = list(field = "data_category",
value = filter$data_category))
filter2$data_type <- list(op = "in",
content = list(field = "data_type",
value = filter$data_type))
filter2$experimental_strategy <- list(op = "in",
content = list(field = "experimental_strategy",
value = filter$experimental_strategy))
filter2$platform <- list(op = "in",
content = list(field = "platform",
value = filter$platform))
names(sampleTypeId) <- NULL # avoid names added into tmp_metadata.json
fieldSampleTypeId <- "cases.samples.sample_type_id"
filterSampleTypeId <- list(op = "in",
content = list(field = fieldSampleTypeId,
value = sampleTypeId))
filterAll <- list(op = "and",
content = list(filter2$access,
filter2$data_format,
filter2$project_id,
filter2$data_category,
filter2$data_type,
filter2$experimental_strategy,
filter2$platform,
filterSampleTypeId))
payload <- list(filters = filterAll,
format = "TSV",
sort = "file_id",
from = 1,
size = entityCount,
fields = paste(fieldsMeta, collapse = ","))
cat(toJSON(payload), file = paste(tmpDir, "/tmp_metadata.json", sep = ""))
stdOut <- system2("curl", arg, stdout = T)
if (!is.null(attr(stdOut, "status"))) {
print("error (download): check the proxy")
}
stopifnot(is.null(attr(stdOut, "status")))
if ("data" %in% dir()) {file.remove("data")}
metaData <- tryCatch(read.csv(out,
sep = "\t",
row.names = NULL,
as.is = T,
na.strings = "",
colClasses = "character"),
error = function(e){print(e$message); return(NULL)})
if (!is.null(metaData)) { # > 0 lines available in input
if (length(grep("\\.1\\.", colnames(metaData))) > 0) {
metaData <- MetaCut(metaData, colPattern = "\\.1\\.")
}
metaCut <- metaData[grep(filter$file_name, metaData$file_name),
sort(colnames(metaData))] # filter with filename
if (nrow(metaCut) == 0) {
metaData <- NULL
} else {
metaCut <- metaCut[order(metaCut$file_name), ] # sort before split !!
if (any(table(metaCut[, filter$submitter_id]) != 1)) { # duplicated files with same barcode
boolRow <- ArchiveNewestInGroups(metaCut$archive.file_name,
metaCut$file_name)
# not filter$submitter_id because of one barcode to multi files
metaCut <- metaCut[boolRow, ]
}
stopifnot(all(table(metaCut[, filter$submitter_id]) == 1)) # duplicated files with same barcode
rownames(metaCut) <- metaCut[, filter$submitter_id]
metaData <- metaCut[order(rownames(metaCut)), order(colnames(metaCut))] # sort by barcode
stopifnot(all(rownames(metaData) == metaData[filter$submitter_id]))
write.table(metaData,
file = paste(tmpDir,
"/tmp_metadata_byType__",
arch,
"__",
endp,
"__",
paste(vCancer, collapse = "_"),
"__",
sAssay,
".tsv",
sep = ""),
quote = F, sep = "\t", col.names = NA, row.names = T)
}
}
print("metadata file: preparing done!")
return(metaData)
}
#' Download files by \code{file_id}
#'
#' @param fileId2Bar Character vector of barcode with file_id as the name.
#' @param tmpDir String of directory for temporary files.
#' @param arch String of archive type: "legacy" or "".
#' @return Character vector of downloaded filename with file_id as the name.
#' @example
#' fileNameById <- FileNameById(metaData$file_id, tmpDir = ".")
FileNameById <- function(fileId2Bar,
tmpDir = ".",
arch = "legacy") {
if (length(fileId2Bar) == 0) { # no files available for this filter
fileNameById <- NULL
} else {
stopifnot(length(fileId2Bar) > 0) # no files available for this filter
library(rjson)
tmpTar <- paste(tmpDir, "/gdc_download_", TimeNow(), ".tar.gz", sep = "")
url <- paste("https://gdc-api.nci.nih.gov/",
arch,
ifelse(arch == "", "", "/"),
"data",
sep = "")
opt <- paste("-o ", tmpTar,
" --silent --show-error --request POST ",
"--header Content-Type:application/json --data @",
tmpDir, "/tmp_id.json",
sep = "")
arg <- paste(opt, url)
cat(toJSON(list(ids = names(fileId2Bar))),
file = paste(tmpDir, "/tmp_id.json", sep = ""))