R/iqrxFilter.R

In avastermark19/doseR_development: Test Package of doseR

#' @title iqrxFilter Function to filter expression data within a countData object.
#' @description This function filters the expression of the supplied countData object. iqrxFilter is a filtering function used to remove rows (genes) of various expression data.
#' @usage iqrxFilter(cD, iqr_multi = 1.5, MEDIAN = FALSE, na.rm = TRUE)
#' @param cD A countData object.
#' @param iqr_multi Numeric multiplier; removes any outliers that are iqr_multi times the mid-50 percentile distance greater or less than the 25th and 75th percentiles, by default
#' @param MEDIAN Boolean, Calculate RowMeans or RowMedians.
#' @param na.rm Boolean, NA removal.
#' @details This function filters the expression of the supplied countData object, based on a selected percentage cutoff and selected interquartile range multiplier. The function iqrxFilter will: (1) log-base two transform all RPKM values (obligatory); (2) remove any outliers that were 1.5 times the mid-50 percentile distance greater or less than the 75th and 25th percentiles (by default), respectively; and (3) uses mean values and instead of median values (by default).
#' @return Returns a filtered countData object.
#' @author AJ Vaestermark, JR Walters.
#' @references Jue et al. BMC Genomics 2013 14:150

iqrxFilter <- function(cD, iqr_multi = 1.5, MEDIAN = FALSE, na.rm = TRUE) {

  if(MEDIAN) {
    #require(matrixStats)
    rpkm <- log2(matrixStats::rowMedians( cD@RPKM, na.rm = na.rm))
  } else {
    rpkm <- log2(rowMeans( cD@RPKM, na.rm = na.rm ))
  }

  interq <- quantile(x = rpkm[is.finite(rpkm)], probs = c(.25, .75) ) # get 25 & 75 quartiles, excluding true 0 values
  iqr <- interq[2] - interq[1] # get interquartile range
  lo.bound <- interq[1] - (iqr * iqr_multi)
  hi.bound <- interq[2] + (iqr * iqr_multi)

  outliers <- which(rpkm < lo.bound | rpkm > hi.bound)

  percent <- function(x, digits = 2, format = "f", ...) { paste0(formatC(100 * x, format = format, digits = digits, ...), "%") }
  pct <- percent(  length(outliers)  / length(rpkm)   )
  message( "Filtering removed ", length(outliers), " (", pct, ") of ", length(rpkm), " total loci." )

  return(cD[-outliers,]) # remove all rows with "outlier" status

}