SegmentCGH:

In brian-bot/rCGH: aCGH-based genomic profiling

Usage

SegmentCGH(object, Smooth = TRUE, UndoSD = NULL, minMarks = 8)

Arguments

object
Smooth
UndoSD
minMarks

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (object, Smooth = TRUE, UndoSD = NULL, minMarks = 8) 
{
    cnSet <- getCNset(object)
    cnSet <- cnSet[order(cnSet$ChrNum, cnSet$ChrStart), ]
    params = getParam(object)
    if (is.null(UndoSD)) 
        params$UndoSD <- 0.25 + sqrt(max(getParam(object3)$SigmaSq))
    else params$UndoSD <- UndoSD
    L2R <- cnSet$Log2Ratio
    Chr <- cnSet$ChrNum
    Pos <- cnSet$ChrStart
    sampleName <- getInfo(object, "sampleName")
    if (is.na(sampleName)) 
        sampleName <- "sample_x"
    cat("Computing standard segmentation...\n")
    segTable <- .computeSegmentation(L2R, Chr, Pos, sampleName, 
        params, Smooth)
    segTable <- .smoothSeg(segTable, minMarks)
    segTable <- .computeMedSegm(segTable, L2R)
    segTable <- .mergeLevels(segTable)
    probeValues.left <- .probeSegValue(segTable, use.medians = TRUE)
    cat("Number of segments:", nrow(segTable), "\n")
    object@param <- params
    object@segTable = segTable
    object@cnSet = cbind.data.frame(cnSet, Segm = probeValues.left)
    return(object)
  }

brian-bot/rCGH documentation built on May 13, 2019, 5:11 a.m.