selectSegments {copynumber} | R Documentation

## Select multipcf segments

### Description

Selects multipcf segments based on a desired characteristic.

### Usage

     selectSegments(segments, what = "variance", thres = NULL, nseg = 10,
                      large = TRUE, p = 0.1)

### Arguments

`segments` | a data frame containing segments found by `multipcf`.
`what` | the desired characteristic to base selection on. Must be one of "variance" (default),"length" and "aberration". See details below.
`thres` | an optional numeric threshold to be applied in the selection.
`nseg` | the desired number of segments to be selected, default is 10. Only used if `thres=NULL`.
`large` | logical value indicating whether segments with large (TRUE) or small (FALSE) variance, length or mean value should be selected when `what` is "variance", "length" or "aberration", respectively.
`p` | a number between 0 and 1 giving the minimum proportion of samples for which an aberration must be detected, default is 0.1. Only applicable if `what="aberration"`.

### Details

The input in `what` determines how the segments are selected. Three options are available:

If `what="variance"` the variance of the segment values across all samples is calculated for each segment. If `thres` is specified, the subset of segments for which the variance is above (if `large=TRUE`) or below (if `large=FALSE`) the threshold is returned. If `thres` is not given by the user, a given number of segments determined by the input in `nseg` is selected; if `large=TRUE` this will be the `nseg` segments with the highest variance, whereas if `large=FALSE` the subset will consist of the `nseg` segments with the lowest variance.

If `what="length"` selection is based on the genomic length of the segments (end position minus start position). If `thres` is specified, the subset of segments for which the length is above (if `large=TRUE`) or below (if `large=FALSE`) this threshold is returned. If `thres` is left unspecified, a given number of segments determined by the input in `nseg` is selected; if `large=TRUE` this will be the `nseg` longest segments, whereas if `large=FALSE` it will be the `nseg` shortest segments.

If `what="aberration"` the aberration frequency is used to select the subset of segments. If `thres` is specified, the proportion of samples for which the segment value is above (if `large=TRUE`) or below (if `large=FALSE`) the threshold is calculated for each segment. The subset of segments where this frequency is above or equal to the proportion set by the parameter `p` is returned. If `thres` is not specified, the `nseg` segments with the highest (1-p)-quantile (if `large=TRUE`) or the lowest p-quantile (if `large=FALSE`) is returned.

### Value

A list containing:

`sel.seg` | data frame containing the selected segments.

In addition, depending on the value of `what`:

`seg.var` | a vector giving the variance for each segment. Only returned if `what = "variance"`.
`seg.length` | a vector giving the length of each segment. Only returned if `what = "length"`.
`seg.ab.prop` | a vector giving the aberration proportion for each segment. Only returned if `what = "aberration"` and `thres` is specified.
`seg.quantile` | a vector giving the (1-p)- or p-quantile for each segment. Only returned if `what = "aberration"` and `thres=NULL`.

### Author(s)

Gro Nilsen

### See Also

`multipcf`

### Examples

    #Lymphoma data
    data(lymphoma)

    #Run multipcf
    segments <- multipcf(lymphoma,gamma=12)

    #Select the 10 segments with the highest variance:
    sel.seg1 <- selectSegments(segments)

    #Select the segments where the variance is below 0.001
    sel.seg2 <- selectSegments(segments,thres=0.001,large=FALSE)

    #Select the 5 longest segments:
    sel.seg3 <- selectSegments(segments,what="length",nseg=5)

    #Select the segments where 20 % of the samples have segment value of 0.2 or more:
    sel.seg4 <- selectSegments(segments,what="aberration",thres=0.2,p=0.2)

    #Select the 20 segments with the largest median:
    sel.seg5 <- selectSegments(segments,what="aberration",nseg=20,p=0.5)

[Package copynumber version 1.26.0 Index]