makeRobustCNVR: Calculates robust CNV regions.

In gpovysil/cn.mops: cn.mops - Mixture of Poissons for CNV detection in NGS data

Calculates robust CNV regions.

Description

This generic function calculates robust CNV regions by segmenting the I/NI call per genomic region of an object CNVDetectionResult-class.

Usage

## S4 method for signature 'CNVDetectionResult'
makeRobustCNVR(object, robust = 0.5,
  minWidth = 4, ...)

Arguments

object	An instance of "CNVDetectionResult"
robust	Robustness parameter. The higher the value, the more samples are required to have a CNV that confirms the CNV region. Setting this parameter to 0 restores the original CNV regions. (Default=0.5)
minWidth	The minimum length measured in genomic regions a CNV region has to span in order to be called. A parameter of the segmentation algorithm. (Default=4).
...	Additional parameters passed to the segmentation algorithm.

Details

This generic function calculates robust CNV regions by segmenting the I/NI call per genomic region of an object CNVDetectionResult-class.

cn.mops usually reports a CNV region if at least one individual has a CNV in this region. For some applications it is useful to find more common CNV regions, i.e., regions in which more than one sample has a CNV. The I/NI call measures both signal strength and how many sample show an abnormal copy number, therefore segmentation of the I/NI call can provide robust CNV regions.

Value

makeRobustCNVR returns a "CNVDetectionResult" object containing new values in the slot "cnvr".

Author(s)

Guenter Klambauer [e-mail]

Examples

data(cn.mops)
r <- cn.mops(X[1:100,1:5])
rr <- calcIntegerCopyNumbers(makeRobustCNVR(r,robust=0.1,minWidth=3))

gpovysil/cn.mops documentation built on Aug. 7, 2024, 12:45 p.m.