Call aberrations in segmented data

Description

Segments, obtained by pcf or multipcf, are classified as "gain", "normal" or "loss" given the specified thresholds.

Usage

callAberrations(segments, thres.gain, thres.loss = -thres.gain)

Arguments

Details

Each region found in segments is classified as "gain", "normal" or "loss". Regions with gain or loss will be those segments where the segment value is above or below the value given in thres.gain or thres.loss, respectively.

Value

A new segment data frame where the segment values have been replaced by the classification "gain", "normal" or "loss".

Author(s)

Gro Nilsen

Examples

#load lymphoma data
data(lymphoma)
#Run pcf
seg <- pcf(data=lymphoma,gamma=12)

#Call gains as segments whose value is > 0.2, and losses as segments whose
# value < -0.1
ab.seg <- callAberrations(seg,thres.gain=0.2,thres.loss=-0.1)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(copynumber)
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, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, 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, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/copynumber/callAberrations.rd_%03d_medium.png", width=480, height=480)
> ### Name: callAberrations
> ### Title: Call aberrations in segmented data
> ### Aliases: callAberrations
> 
> ### ** Examples
> 
> #load lymphoma data
> data(lymphoma)
> #Run pcf
> seg <- pcf(data=lymphoma,gamma=12)
pcf finished for chromosome arm 1p 
pcf finished for chromosome arm 1q 
pcf finished for chromosome arm 2p 
pcf finished for chromosome arm 2q 
pcf finished for chromosome arm 3p 
pcf finished for chromosome arm 3q 
pcf finished for chromosome arm 4p 
pcf finished for chromosome arm 4q 
pcf finished for chromosome arm 5p 
pcf finished for chromosome arm 5q 
pcf finished for chromosome arm 6p 
pcf finished for chromosome arm 6q 
pcf finished for chromosome arm 7p 
pcf finished for chromosome arm 7q 
pcf finished for chromosome arm 8p 
pcf finished for chromosome arm 8q 
pcf finished for chromosome arm 9p 
pcf finished for chromosome arm 9q 
pcf finished for chromosome arm 10p 
pcf finished for chromosome arm 10q 
pcf finished for chromosome arm 11p 
pcf finished for chromosome arm 11q 
pcf finished for chromosome arm 12p 
pcf finished for chromosome arm 12q 
pcf finished for chromosome arm 13q 
pcf finished for chromosome arm 14q 
pcf finished for chromosome arm 15q 
pcf finished for chromosome arm 16p 
pcf finished for chromosome arm 16q 
pcf finished for chromosome arm 17p 
pcf finished for chromosome arm 17q 
pcf finished for chromosome arm 18p 
pcf finished for chromosome arm 18q 
pcf finished for chromosome arm 19p 
pcf finished for chromosome arm 19q 
pcf finished for chromosome arm 20p 
pcf finished for chromosome arm 20q 
pcf finished for chromosome arm 21q 
pcf finished for chromosome arm 22q 
pcf finished for chromosome arm 23p 
pcf finished for chromosome arm 23q 
> 
> #Call gains as segments whose value is > 0.2, and losses as segments whose
> # value < -0.1
> ab.seg <- callAberrations(seg,thres.gain=0.2,thres.loss=-0.1)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>