groupCNVs {CNVrd2} | R Documentation

## Cluster segmentation scores into groups.

### Description

Use the EM algorithm (Dempster et al., 1977) to cluster segmentation scores into various groups.

### Usage

    groupCNVs(Object, ...)

### Arguments

`Object` | An object of class clusteringCNVs.
`...` | Further arguments.

### Details

Users can set limits of segmentation scores: values being smaller than the left limit will be assigned to the smallest group and values being larger than righ limit will be assigned to the largest group.

### Value

`allGroups` | Samples and their corresponding groups
`means` | Means of groups.
`sigma` | Variances of groups.
`p` | Proportions of groups in all data set.
`loglk` | Value of loglikehood function.

### Author(s)

Hoang Tan Nguyen, Tony R Merriman and MA Black. hoangtannguyenvn@gmail.com

### References

Dempster, A. P., Laird, N. M., Rubin, D. B., 1977. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society. Series B (Methodological), 1-38.

### See Also

`emnormalCNV`, `searchGroupCNVs`

### Examples

    data("fcgr3bMXL")
    #resultSegment <- segmentSamples(Object = objectCNVrd2, stdCntMatrix = readCountMatrix)
    objectCluster <- new("clusteringCNVs",
                         x = resultSegment$segmentationScores[, 1], k = 4, EV = TRUE)

    #searchGroupCNVs(Object = objectCluster)
    copynumberGroups <- groupCNVs(Object = objectCluster)

[Package CNVrd2 version 1.18.0 Index]