makeRobustCNVR {cn.mops} | R Documentation

## 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 klambauer@bioinf.jku.at

### Examples

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

[Package cn.mops version 1.32.0 Index]