R/filterMaf.R

In maftools: Summarize, Analyze and Visualize MAF Files

#' Filter MAF objects
#'
#' @description Filter MAF by genes or samples
#' @param maf an MAF object generated by \code{\link{read.maf}}
#' @param tsb remove these samples (Tumor Sample Barcodes)
#' @param genes remove these genes
#' @param isTCGA FALSE
#' @return Filtered object of class \code{\link{MAF-class}}
#' @seealso \code{\link{subsetMaf}}
#' @examples
#' laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
#' laml <- read.maf(maf = laml.maf)
#' #get rid of samples of interest
#' filterMaf(maf = laml, tsb = c("TCGA-AB-2830", "TCGA-AB-2804"))
#' #remove genes of intrest
#' filterMaf(maf = laml, genes =c("TTN", "AHNAK2"))
#' @export
filterMaf = function(maf, genes = NULL, tsb = NULL, isTCGA = FALSE){

  if(all(c(is.null(tsb), is.null(genes)))){
    stop("Please provide sample names or genes or a query or ranges to subset by.")
  }

  #Synonymous variants
  maf.silent <- maf@maf.silent
  #Main data
  maf.dat <- maf@data
  #Annotations
  maf.anno <- data.table::copy(x = maf@clinical.data)
  nrows_nsyn = nrow(maf.dat)
  nrows_syn = nrow(maf.silent)

  #Select
  if(!is.null(tsb)){
    #message("-subsetting by tumor sample barcodes..")
    tsb = as.character(tsb)
    if(isTCGA){
      tsb = substr(x = tsb, start = 1, stop = 12)
    }
    maf.dat = maf.dat[!Tumor_Sample_Barcode %in% tsb,]
    maf.silent = maf.silent[!Tumor_Sample_Barcode %in% tsb,]
    message("Removed ", (nrows_syn+nrows_nsyn) - (nrow(maf.dat) + nrow(maf.silent)), " variants from ", length(tsb), " samples")
  }

  if(!is.null(genes)){
    #message("-subsetting by genes..")
    genes = as.character(genes)
    maf.dat = maf.dat[!Hugo_Symbol %in% genes, ]
    maf.silent = maf.silent[!Hugo_Symbol %in% genes, ]
    message("Removed ", (nrows_syn+nrows_nsyn) - (nrow(maf.dat) + nrow(maf.silent)), " variants from ", length(genes), " genes")
  }

  maf.silent = droplevels.data.frame(maf.silent)
  maf.dat = droplevels.data.frame(maf.dat)
  maf.anno = droplevels.data.frame(maf.anno)

  mafSummary = summarizeMaf(maf.dat, chatty = FALSE, anno = maf.anno)

  MAF(data = maf.dat, variants.per.sample = mafSummary$variants.per.sample, variant.type.summary = mafSummary$variant.type.summary,
          variant.classification.summary = mafSummary$variant.classification.summary, gene.summary = mafSummary$gene.summary,
          summary = mafSummary$summary, maf.silent = maf.silent, clinical.data = droplevels(mafSummary$sample.anno))
}