R/RunCNV.R

In findlaycopley/PlotCNV: Plot a pretty copynumber plot

#' Run the whole pipeline start to finish
#' This function will take a dataframe with sample, chr, start.pos, end.pos and call.
#' It will create an instance of the CNVvault class
#' Then it will order this class based on the total amount of the geneome editted.
#' Then it will generate the positions for each sample on the y-axis
#' Then it will plot the output
#' @name RunCNV
#' @title RunCNV
#' @param Copynumber Dataframe of your segments. REQUIRED
#' @param genome The genome to use for plotting. Currently only works on hg19. Default: "hg19"
#' @param chr string: name of the column for the chromosome. Default: "chr"
#' @param sampleID string: name of the column for the sample IDs. Default: "sampleID"
#' @param start.pos string: name of the column for the start positions of the segments. Default: "start.pos"
#' @param end.pos string: name of the column for the end positions of the segments. Default: "end.pos"
#' @param calls string: name of the column for the SV type of the segments. Default: "calls"
#' @keywords Copynumber CNV
#' @export
#' @examples
#' CNV <- generateTestData()
#' RunCNV(CNV)
#' ## If you have differnet column names specify them when calling the function
#' RunCNV(CNV, chr="CHROM","start.pos" = "Start", sampleID="sample")
#'
#' ## You can run the functions seperately too:
#' CNV <- prepareCNV(Copynumber, chr=chr, sampleID=sampleID, start.pos=start.pos, end.pos=end.pos, calls=calls)
#' CNV <- orderCNV(ReturnClass)
#' CNV <- setPositionsCNV(ReturnClass, genome=genome)
#' CNV <- plotCopynumber(ReturnClass)
#'

RunCNV <- function(Copynumber, ...) {
        ReturnClass <- prepareCNV(Copynumber, ...)
        ReturnClass <- orderCNV(ReturnClass, ...)
        ReturnClass <- setPositionsCNV(ReturnClass, ...)
        ReturnClass <- plotCopynumber(ReturnClass, ...)
        ReturnClass
}