normalizeSegmentedBins: Normalize segmented bins
In QDNAseq: Quantitative DNA Sequencing for Chromosomal Aberrations

Description Usage Arguments Details Value Author(s) See Also Examples

Normalize segmented bins.

1	normalizeSegmentedBins(object, inter=c(-0.1, 0.1), force=FALSE)

`object`	An object of class QDNAseqCopyNumbers.
`inter`	The interval in which the function should search for the normal level.
`force`	Whether to force execution when it causes removal of downstream calling results.

This function recursively searches for the interval containing the most segmented data, decreasing the interval length in each recursion. The recursive search makes the post-segmentation normalization robust against local maxima. This function is particularly useful for profiles for which, after segmentation, the 0-level does not coincide with many segments. It is more or less harmless to other profiles. We advise to keep the search interval (inter) small, in particular at the positive (gain) side to avoid that the 0-level is set to a common gain level.

Returns an object of class QDNAseqCopyNumbers with re-normalized data.

Ilari Scheinin

Internally, postsegnormalize of the CGHcall package is used.

data(LGG150)
readCounts <- LGG150
readCountsFiltered <- applyFilters(readCounts)
readCountsFiltered <- estimateCorrection(readCountsFiltered)
copyNumbers <- correctBins(readCountsFiltered)
copyNumbersNormalized <- normalizeBins(copyNumbers)
copyNumbersSmooth <- smoothOutlierBins(copyNumbersNormalized)
copyNumbersSegmented <- segmentBins(copyNumbersSmooth)
copyNumbersSegmented <- normalizeSegmentedBins(copyNumbersSegmented)