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Select multipcf segments

Source: R/selectSegments.r
selectSegments.Rd

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".

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.

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.

See also

multipcf()

Author

Gro Nilsen

Examples


#Lymphoma data
data(lymphoma)

#Run multipcf
segments <- multipcf(lymphoma,gamma=12)
#> multipcf finished for chromosome arm 1p 
#> multipcf finished for chromosome arm 1q 
#> multipcf finished for chromosome arm 2p 
#> multipcf finished for chromosome arm 2q 
#> multipcf finished for chromosome arm 3p 
#> multipcf finished for chromosome arm 3q 
#> multipcf finished for chromosome arm 4p 
#> multipcf finished for chromosome arm 4q 
#> multipcf finished for chromosome arm 5p 
#> multipcf finished for chromosome arm 5q 
#> multipcf finished for chromosome arm 6p 
#> multipcf finished for chromosome arm 6q 
#> multipcf finished for chromosome arm 7p 
#> multipcf finished for chromosome arm 7q 
#> multipcf finished for chromosome arm 8p 
#> multipcf finished for chromosome arm 8q 
#> multipcf finished for chromosome arm 9p 
#> multipcf finished for chromosome arm 9q 
#> multipcf finished for chromosome arm 10p 
#> multipcf finished for chromosome arm 10q 
#> multipcf finished for chromosome arm 11p 
#> multipcf finished for chromosome arm 11q 
#> multipcf finished for chromosome arm 12p 
#> multipcf finished for chromosome arm 12q 
#> multipcf finished for chromosome arm 13q 
#> multipcf finished for chromosome arm 14q 
#> multipcf finished for chromosome arm 15q 
#> multipcf finished for chromosome arm 16p 
#> multipcf finished for chromosome arm 16q 
#> multipcf finished for chromosome arm 17p 
#> multipcf finished for chromosome arm 17q 
#> multipcf finished for chromosome arm 18p 
#> multipcf finished for chromosome arm 18q 
#> multipcf finished for chromosome arm 19p 
#> multipcf finished for chromosome arm 19q 
#> multipcf finished for chromosome arm 20p 
#> multipcf finished for chromosome arm 20q 
#> multipcf finished for chromosome arm 21q 
#> multipcf finished for chromosome arm 22q 
#> multipcf finished for chromosome arm 23p 
#> multipcf finished for chromosome arm 23q 

#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)