comparison cluster.tools/fix.and.merge.TCGA.sample.IDs.R @ 0:0decf3fd54bc draft

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0:0decf3fd54bc

#!/usr/bin/env Rscript
argspec <- c("fix.and.merge.TCGA.samples.IDs.R takes a clustering from ConsensusClusterPlus and clinical survival data
and generates a KM-plot, along with the log-rank p-values

        Usage: 
                fix.and.merge.TCGA.samples.IDs.R -d <data.file> 

                \n\n")
args <- commandArgs(TRUE)
if ( length( args ) == 1 && args =="--help") { 
  write(argspec, stderr())
  q();
}

lib.load.quiet <- function( package ) {
   package <- as.character(substitute(package))
   suppressPackageStartupMessages( do.call( "library", list( package=package ) ) )
}
lib.load.quiet(getopt)

spec <- matrix( c( "data.fname",      "d", 1, "character",
                   "num.components",  "n", 2, "integer",
                   "remove.normals",  "r", 0, "logical",
                   "output.fname",    "o", 2, "character"
                   ),
                nc=4,
                byrow=TRUE
               )

opt <- getopt( spec=spec )

data <- as.matrix( read.delim( opt$data.fname, row.names=1, check.names=FALSE ) )
if ( is.null( opt$num.components ) ) { opt$num.components <- 3 }
if ( is.null( opt$remove.normals ) ) { opt$remove.normals <- FALSE }
if ( is.null( opt$output.fname ) ) { opt$output.fname <- paste( "sample.IDs.updated", basename( opt$data.fname ), sep="." ) }

if ( opt$num.components < 3 ) {
  err.msg <- "Minimum number of barcode components that can be used is 3\n"
  cat( err.msg, file=opt$output.fname )
  stop( err.msg )
}

remove.periods.from.ids <- function( ids ) {
  return( gsub( "\\.", "-", ids ) )
}


reformat.ids <- function( ids,
                          num.components=3 ) {
  return( sapply( strsplit( ids, "-" ), function(x) paste( x[1:num.components], collapse="-" ) ) )
}


merge.cols <- function( mat,
                        samp.ids ) {

  if ( ! any( duplicated( samp.ids ) ) ) {
    colnames( mat ) <- samp.ids
    return( mat )
  }

  dupes <- unique( samp.ids[ duplicated( samp.ids ) ] )
  uniqs <- samp.ids[ ! samp.ids %in% dupes ]

  uniq.mat <- mat[ , ( samp.ids %in% uniqs ), drop=FALSE ]
  colnames( uniq.mat ) <- uniqs

  for ( dup in dupes ) {
    dup.mat <- apply( mat[, ( samp.ids %in% dup ), drop=FALSE],
                      1,
                      mean,
                      na.rm=TRUE )
    
    uniq.mat <- cbind( uniq.mat, dup.mat )
  }
  colnames( uniq.mat ) <- c( uniqs, dupes )
  return( uniq.mat )
}


cnames <- colnames( data )
rnames <- rownames( data )

transpose.back <- FALSE

if ( all( grepl( "^TCGA", rnames ) ) ) {
  data <- t( data )
  transpose.back <- TRUE
} else {
  if ( ! all( grepl( "^TCGA", cnames ) ) ) {
    err.msg <- "can't find any TCGA samples listed in this matrix.  If columns are samples, all columns must be a TCGA sample ID.  Same if rows are samples.\n"
    cat( err.msg, file=opt$output.fname )
    stop( err.msg )
  }
}

cnames <- remove.periods.from.ids( colnames( data ) )
nelts <- as.numeric( names( table( as.factor( sapply( strsplit( cnames, "-" ), function(x) length(x ) ) ) ) ) )
if ( length( nelts ) > 1 ) {
  err.msg <- "Error: Inconsistent TCGA sample barcodes used.  Have found ID with different numbers of components in the barcodes used\n" 
    cat( err.msg, file=opt$output.fname )
    stop( err.msg )
}

if ( opt$remove.normals ) {
  if ( nelts > 3 ) {
    normals <- grepl( "^TCGA-..-....-1", cnames )
    data <- data[ , (! normals ), drop=FALSE ]
  }
}

if ( opt$num.components < nelts ) {
  cnames <- reformat.ids( ids=cnames, num.components=opt$num.components )
  data <- merge.cols( data, cnames )
}

if ( transpose.back ) data <- t( data )

write.table( data, opt$output.fname, sep="\t", quote=FALSE, col.names=NA )