ChAMP (version 1.10.0)

champ.CNA: Inference of Copy Number Abberrations from intensity values.

Description

This function enables CNA profiles to be built using methylation data from Illumina HumanMethylation450 BeadChips.

Usage

champ.CNA(intensity = myLoad$intensity, pd = myLoad$pd, loadFile = FALSE, batchCorrect = TRUE, 
file = "intensity.txt", resultsDir = paste(getwd(), "resultsChamp", sep = "/"), 
sampleCNA=TRUE, plotSample=TRUE, filterXY = TRUE, groupFreqPlots=TRUE,freqThreshold=0.3,
control=TRUE,controlGroup="Control",arraytype="450K")

Arguments

intensity

A matrix of intensity values for each sample. The default assumes you ran champ.load and saved the output to "myLoad".

pd

This data.frame includes the information from the sample sheet. The default assumes you ran champ.load and saved the output to "myLoad".

loadFile

If loadFile=TRUE, intensity data will be loaded from a separate file. Default is FALSE.

batchCorrect

If batchCorrect=TRUE ComBat will be run on the data to correct for batch effects due to sentrixID/slide number. Default is TRUE.

file

If loadFile=T this is the name of the file with the intensity values. Default is "intensity.txt".

resultsDir

Directory where results will be saved. Default is a folder in the current working directory called "resultsChamp".

sampleCNA

If sampleCNA=TRUE, then . Default is TRUE.

plotSample

If sampleCNA=TRUE and plotSample=TRUE, then CNA plots will be saved for each sample. Default is TRUE.

filterXY

Probes from X and Y chromosomes are removed. Default is TRUE.

groupFreqPlots

If groupFreqPlots=T, then

freqThreshold

If groupFreqPlots=T, then freqThreshold will be used as the cutoff for calling a gain or loss. Default is 0.03.

control

If control=T, then the samples defined by the controlGroup identifier will be used as the baseline for CNA calculations. Default is TRUE.

controlGroup

If Control=T, then controlGroup will be used as the baseline for CNA calculations. The default is "Control". Control samples must be labelled with this identifier in the Sample_Group column of the pd file. If this doesn't exist in your dataset then ChAMP will revert to using the internal blood controls "champCtls"'

arraytype

Choose microarray type is 450K or EPIC.

References

Feber, A et. al. (2014). CNA profiling using high density DNA methylation arrays. Genome Biology.

Examples

	data(testDataSet)
	data(champBloodCtls)
	myLoad=testDataSet
	champ.CNA(batchCorrect=FALSE,sampleCNA=FALSE,groupFreqPlots=FALSE)