R/output_list_function.R

In iCNV: Integrated Copy Number Variation detection

#' Generate ouput list.
#' 
#' Generate human readable output from result calculated by iCNV_detection function
#' 
#' @importFrom grDevices colorRampPalette dev.off pdf
#' @importFrom graphics axis grid legend par plot points
#' @importFrom stats aggregate dnorm dunif kmeans sd
#' @importFrom utils read.table write.table
#' @param icnv_res CNV inference result. Output from iCNV_detection()
#' @param sampleid the name of the sample, same order as the input
#' @param CN An indicator variable with value {0,1} for whether exact copy number inferred in iCNV_detection. 0 no exact CN, 1 exact CN. Type integer. Default 0.
#' @param min_size A integer which indicate the minimum length of the CNV you are interested in. This could remove super short CNVs due to noise. Type integer. Default 0. Recommend 1000.
#' @return output CNV list of each individual
#' @examples
#' icnv.output <- output_list(icnv_res=icnv_res0,sampleid=sampname_qc, CN=0)
#' @export
output_list <- function(icnv_res,sampleid=NULL,CN=0,min_size=0){
  stopifnot(is.numeric(CN))
  stopifnot(is.numeric(min_size))
  if (CN!=0){
    testres <- icnv_res[[1]]
    result <- lapply(icnv_res[[2]],function(x){x})
    Lpos <- lapply(testres,function(x){x[[2]]})
  }
  else{
    testres <- icnv_res[[1]]
    result <- lapply(testres,function(x){x[[1]]})
    Lpos <- lapply(testres,function(x){x[[2]]})
  }
  if(is.null(sampleid)){
      sampleid <- seq(1,length(testres))
  }
  # extract CNV region
  res <- mapply(function(I,pos){
    It <- I
    post <- pos
    i <- 2
    while(i<=length(It)){
      if (It[i]!=2 & It[i]==It[i-1]){
        It <- It[-i]
        temp <- post[i,2]
        post[i-1,2] <- temp
        post <- post[-i,]
      }
      else{
        i <- i+1
      }
    }
    return(list(It,post))
  },result,Lpos,SIMPLIFY = FALSE)

  icnv_res <- mapply(function(res){
    cnv <- res[[1]]
    pos <- res[[2]]
    ind <-  cnv!=2
    cnv <- cnv[ind]
    pos <- matrix(pos[ind,],ncol=2)
    filt <- (pos[,2]-pos[,1]>=min_size)
    cnv <- cnv[filt]
    pos <- matrix(pos[filt,],ncol=2)
    return(cbind(cnv,pos))
  },res,SIMPLIFY = TRUE)

  names(icnv_res) <- sampleid
  return(icnv_res)
}