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export joinSegmentNeighbours and update docs
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R/methSeg.R

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@@ -141,7 +141,7 @@ methSeg<-function(obj, diagnostic.plot=TRUE, join.neighbours=FALSE, ...){
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# if joining, show clustering after joining
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if(join.neighbours) {
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message("joining neighbouring segments")
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seg.res <- .joinSegmentNeighbours(seg.res)
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seg.res <- joinSegmentNeighbours(seg.res)
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diagnostic.plot=TRUE
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# get the new density
@@ -308,10 +308,13 @@ colramp=colorRamp(c("gray","green", "darkgreen"))
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#}
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#' Join directly neighbouring segments of same class
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#' Join directly neighbouring segments produced by methSeg
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#'
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#'
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# @param res object returned from a methSeg call
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#' Segmentation and clustering are two distinct steps in methSeg(),
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#' leading to adjacent segments of the same class.
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#' This leads to a bias segment length distributions,
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#' which is removed by joining those neighbours.
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#'
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#' @param res A \code{\link[GenomicRanges]{GRanges}} object with segment
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#' classification and information prudoced by \code{\link{methSeg}}
@@ -325,13 +328,13 @@ colramp=colorRamp(c("gray","green", "darkgreen"))
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#' @importFrom data.table copy ":="
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# @noRd
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# @examples
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.joinSegmentNeighbours <- function(res) {
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joinSegmentNeighbours <- function(res) {
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# require(data.table)
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if (length(unique(seqnames(res))) > 1 ) {
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## call recursively for multiple chromosomes
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gr <- lapply(split(res,seqnames(res)),.joinSegmentNeighbours)
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gr <- lapply(split(res,seqnames(res)),joinSegmentNeighbours)
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gr <- do.call(c, unlist(gr,use.names = FALSE) )
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return( gr )
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}

man/joinSegmentNeighbours.Rd

Lines changed: 25 additions & 0 deletions
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man/methSeg.Rd

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