superFreq (version 1.2.3)

cohortAnalyseBatchContrast: Analyse individuals for reccuring mutations

Description

Analyse individuals for reccuring mutations

Usage

cohortAnalyseBatchContrast(metaDataFile, outputDirectories, project,
  subgroups1, subgroups2, name, cpus = 1, onlyDNA = T,
  clonalityCut = 0.4, excludeSamples = c(), excludeIndividuals = c(),
  cosmicDirectory = "", analysisName = "cohortAnalysis",
  cnvWeight = 1, forceRedoVariants = F, forceRedoMean = F,
  forceRedoMatrixPlot = F, forceRedoMeanPlot = F, genome = "hg19",
  ignoreCNAonly = F)

Arguments

metaDataFile

character: path to the metaData file.

outputDirectories

A named list of output directories, containing the entries Rdirectory and plotDirectory where the saved data and plots will be stored respectively.

project

character: The project containing the subgroups.

name

character: The name of the comparison. This names the output directory.

cpus

integer: the maximum number of cpus to run on.

clonalityCut

numeric: the minimum required clonality to be included in the analysis. Deafult 0.4.

excludeSamples

character: The samples to be excluded from the analysis. Default c().

excludeIndividuals

character: The individuals to be excluded from the analysis. Default c().

cosmicDirectory

character: The directory with the COSMIC data.

analysisName

character: The name of the directory where the analysis results are saved. Default "cohortAnalysis".

forceRedoVariants

boolean: Force redo the merging of the variants between individuals. Default FALSE.

forceRedoMean

boolean: Force redo the mean CNAs ans SNVs rates over individuals. Default FALSE.

forceRedoMatrixPlot

boolean: Force redo the hit matrix plot. Default FALSE.

forceRedoMeanPlot

boolean: Force redo the mean CNA plot. Default FALSE.

genome

character: the genome being studied. Default "hg19".

subgroup1

character: The first subgroup(s).

subgroup2

character: The second subgroup(s).

Details

This function calculates mutation rates over genes, both protein changing SNVs, as well as CNA rates for complete loss, loss, gain (3 copies) and amplification (4 or more copies). It also track biallelic loss of genes in samples, by complete loss, a protein changing SNV plus a loss, or two SNVs (that are assumed to be on different alleles). Output is a plot over the genome of the CNA rates, as well as a "top table" of frequently mutated genes. It is run as an afterburner, and needs a finished superFreq analysis to be run on the samples.

Examples

# NOT RUN {
metaDataFile = '/absolute/path/to/metaData.txt'

Rdirectory = '/absolute/path/to/R'
plotDirectory = '/absolute/path/to/plots'

cpus=6
genome = 'hg19'

outputDirectories = list('Rdirectory'=Rdirectory, 'plotDirectory'=plotDirectory)

cohortAnalyseBatch(metaDataFile, outputDirectories, cpus=cpus, genome=genome)

# }