cnSegmentation {sesame} | R Documentation

## Perform copy number segmentation

### Description

Perform copy number segmentation using the signals in the signal set. The function takes a `SigDF` for the target sample and a set of normal `SigDF` for the normal samples. An optional arguments specifies the version of genome build that the inference will operate on. The function outputs an object of class `CNSegment` with signals for the segments ( seg.signals), the bin coordinates ( bin.coords) and bin signals (bin.signals).

### Usage

    cnSegmentation(sdf, sdfs.normal = NULL, refversion = c("hg19", "hg38"))

### Arguments

`sdf` | `SigDF`
`sdfs.normal` | a list of `SigDF`s for normalization, if not given, use the stored normal data from sesameData. However, we do recommend using a matched copy number normal dataset for normalization.
`refversion` | hg19 or hg38

### Value

an object of `CNSegment`

### Examples

    sesameDataCache("EPIC") # in case not done yet
    sdf <- sesameDataGet('EPIC.1.SigDF')
    sdfs.normal <- sesameDataGet('EPIC.5.SigDF.normal')[1:3]
    seg <- cnSegmentation(sdf, sdfs.normal)

    # release memory for Windows package builder
    rm(list=ls(env=sesameData:::cacheEnv), envir=sesameData:::cacheEnv)
    gc()

[Package sesame version 1.12.9 Index]