Description Usage Arguments Value Author(s) See Also Examples
View source: R/determineOffset.R
The composition of a library influences the resulting read densities. To adjust the modelled mean (in the Poisson model) for these composition effects, we estimate a normalising factor f that accounts simultaneously for overall sequencing depth and composition. The derivation of this offset is motivated by the M (log ratio) versus A (averagelogcount) plot.
1 2 
x 

quantile 
quantile q to restrict values of A = log2(sampleInterest*control)/2 
controlPlot 
list defining whether a MA plot should be shown.

A BayMethList
object given as input, where the slot fOffset
is filled accordingly.
Andrea Riebler
maPlot, plotSmear
1 2 3 4 5 6 7 8 9 10 11  if(require(BSgenome.Hsapiens.UCSC.hg18)){
windows < genomeBlocks(Hsapiens, chrs="chr21", width=100, spacing=100)
cpgdens < cpgDensityCalc(windows, organism=Hsapiens,
w.function="linear", window=700)
co < matrix(rnbinom(length(windows), mu=10, size=2), ncol=1)
sI < matrix(rnbinom(2*length(windows), mu=5, size=2), ncol=2)
bm < BayMethList(windows=windows, control=co, sampleInterest=sI,
cpgDens=cpgdens)
bm < determineOffset(bm, controlPlot=list(show=TRUE, mfrow=c(1,2)))
}

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