run.cin.chr: Calculate chromosome CIN
In ICBI/CINdex: Chromosome Instability Index

Description Usage Arguments Value See Also Examples

View source: R/run.cin.chr.R

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.

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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"))

`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'

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

See accompanying vignette for end-to-end tutorial

# 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