Calculate chromosome CIN

Description

run.cin.chr calculates chromosome level CIN for the following default thresholds (with and without normalization): (a) gain threshold 2.5 and loss threshold 1.5 (b) gain threshold 2.25 and loss threshold 1.75 (c) gain threshold 2.10 and loss threshold 1.90. For each of these threshold settings, this function will calculate CIN for gains, losses, and a combination of gains and losses (referred to as 'sum' or 'overall' CIN). This will allow user to examine and select the best setting of gain and loss threshold for their data. More details and tutorial are given in the accompanying vignette.

Usage

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run.cin.chr(grl.seg, out.folder.name = "output_chr_cin", thr.gain = c(2.5,
  2.25, 2.1), thr.loss = c(1.5, 1.75, 1.9), V.def = 2:3, V.mode = c("sum",
  "amp", "del"))

Arguments

grl.seg

The result of any segmentation algorithm such as CBS,FMR. Should be a data frame of 3 column-lists or matrix of three-column lists

out.folder.name

Name of output folder, where the CIN ojbects for each setting will be created

thr.gain

A numeric list that contains values set as threshold gain

thr.loss

A numeric list that contains values set as threshold loss

V.def

An integer vector that has different CIN definitions (2 means normalized, 3 means un-normalized)

V.mode

A vector that has 3 options: 'sum', 'amp' and 'del'

Value

Creates a dataMatrix R object for each setting that contains CIN values

See Also

See accompanying vignette for end-to-end tutorial

Examples

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# Run chromosome level CIN calculation for all thresholds. This is how command should be run:
# A number of RData objects will be created in 'output_chr' folder.
## Not run: 
run.cin.chr(grl.seg = grl.data)

## End(Not run)

#For this example, we run this function for one threshold only

data("grl.data")
run.cin.chr(grl.seg = grl.data, thr.gain=2.25, thr.loss=1.75, V.def=3, V.mode="sum")

# Next step: Plot chromosome level heatmap \code{\link{comp.heatmap}}
# More details and tutorial are given in the accompanying vignette