segmentationHclust {PureCN} | R Documentation

## Minimal segmentation function

### Description

A minimal segmentation function useful when segmentation was performed by third-pary tools. When a `CollapsedVCF` with germline SNPs is provided, it will cluster segments using `hclust`. Otherwise it will use the segmentation as provided. This function is called via the `fun.segmentation` argument of `runAbsoluteCN`. The arguments are passed via `args.segmentation`.

### Usage

    segmentationHclust(seg, vcf = NULL, tumor.id.in.vcf = 1,
      normal.id.in.vcf = NULL, prune.hclust.h = NULL,
      prune.hclust.method = "ward.D", chr.hash = NULL, ...)

### Arguments

`seg` | If segmentation was provided by the user, this data structure will contain this segmentation. Useful for minimal segmentation functions. Otherwise PureCN will re-segment the data. This segmentation function ignores this user provided segmentation.
`vcf` | Optional `CollapsedVCF` object with germline allelic ratios.
`tumor.id.in.vcf` | Id of tumor in case multiple samples are stored in VCF.
`normal.id.in.vcf` | Id of normal in in VCF. Currently not used.
`prune.hclust.h` | Height in the `hclust` pruning step. Increasing this value will merge segments more aggressively. If NULL, try to find a sensible default.
`prune.hclust.method` | Cluster method used in the `hclust` pruning step. See documentation for the `hclust` function.
`chr.hash` | Mapping of non-numerical chromsome names to numerical names (e.g. chr1 to 1, chr2 to 2, etc.). If `NULL`, assume chromsomes are properly ordered.
`...` | Currently unused arguments provided to other segmentation functions.

### Value

`data.frame` containing the segmentation.

### Author(s)

Markus Riester

### See Also

`runAbsoluteCN`

### Examples

    vcf.file <- system.file("extdata", "example.vcf.gz",
        package="PureCN")
    interval.file <- system.file("extdata", "example_intervals_tiny.txt",
        package="PureCN")
    seg.file <- system.file('extdata', 'example_seg.txt',
        package = 'PureCN')

    res <- runAbsoluteCN(seg.file=seg.file, fun.segmentation=segmentationHclust,
        max.ploidy = 4, vcf.file=vcf.file,
        test.purity = seq(0.3, 0.7, by = 0.05), max.candidate.solutions=1,
        genome='hg19', interval.file=interval.file)

[Package PureCN version 1.14.3 Index]