segmentData: Breakpoint detection for arrayCGH data.

In CGHcall: Calling aberrations for array CGH tumor profiles.

Description

A wrapper function to run existing breakpoint detection algorithms on arrayCGH data. Currently only DNAcopy is implemented.

Usage

segmentData(input, clen=10, relSDlong=3, method = "DNAcopy", ...)

Arguments

input	Object of class cghRaw.
clen	Boundary for short vs long segments, in number of features
relSDlong	Relative undo sd for long segments. See details.
method	The method to be used for breakpoint detection. Currently only DNAcopy is supported, which will run the segment function.
...	Arguments for segment.

Details

See segment for details on the algorithm. About clen and relSDlong: these are only relevant when segment option undo.splits=sdundo is set, in combination with segment option undo.SD. relSDlong provides the undo sd for long segments, which equals undo.SD/relSDlong. undo.SD is then used for short segments. In the example below, short segments are considered to contain less or equal to clen=10 features. The example below undoes splits for two consecutive short segments if these are less than undo.SD=3 sd apart, while it undoes splits for two long segments if these are less than undo.SD/relSDlong=3/3=1 sd apart. If, for two consecutive segements, one is short and one is long, splits are undone in the same way as for two short segments.

Value

This function returns a dataframe in the same format as the input with segmented arrayCGH data.

Author(s)

Sjoerd Vosse & Mark van de Wiel

References

Venkatraman, A.S., Olshen, A.B. (2007). A faster circulary binary segmentation algorithm for the analysis of array CGH data. Bioinformatics, 23, 657-663.

Examples

  data(WiltingNorm)
  ## Not run: segmented.data <- segmentData(WiltingNorm, alpha=0.02,clen=10,relSDlong=3,undo.SD=3,undo.splits="sdundo")

Example output

Loading required package: impute
Loading required package: DNAcopy
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: CGHbase
Loading required package: marray
Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: snowfall
Loading required package: snow

Attaching package: 'snow'

The following objects are masked from 'package:BiocGenerics':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, clusterSplit, parApply, parCapply,
    parLapply, parRapply, parSapply

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, clusterSplit, makeCluster, parApply,
    parCapply, parLapply, parRapply, parSapply, splitIndices,
    stopCluster


Attaching package: 'CGHcall'

The following object is masked from 'package:BiocGenerics':

    normalize

CGHcall documentation built on Nov. 8, 2020, 11:12 p.m.