aCGH (version 1.50.0)

find.genomic.events: Finds the genomic events associated with each of the array CGH samples

Description

Finds the genomic events associated with each of the array CGH samples. Events include whole chromosomal gains and losses, aberrations, transitions, amplifications and their respective counts and sizes. The hmm states has to be computed before using this function.

Usage

find.genomic.events(aCGH.obj, maxChrom = 23, factor = 5, maxClones = 1, maxLen = 1000, absValSingle = 1, absValRegion = 1, diffVal1 = 1, diffVal2 = .5, maxSize = 10000, pChrom.min = .9, medChrom.min = .1)

Arguments

aCGH.obj

Object of class aCGH.

maxChrom

Highest chromosomal number to find events.

factor

Determines outliers. See findOutliers.func.

maxClones

Determines aberrations. See findAber.func.

maxLen

Determines aberrations. See findAber.func.

absValSingle

Determines amplifications. See findAmplif.func.

absValRegion

Determines amplifications. See findAmplif.func.

diffVal1

Determines amplifications. See findAmplif.func.

diffVal2

Determines amplifications. See findAmplif.func.

maxSize

Determines amplifications. See findAmplif.func.

pChrom.min

Determines whole chromosomal gains and losses. Chromosome should contain no transitions, have its absolute median equal or greater than medChrom.min and at least medChrom.min has to be greater or less than 0.

medChrom.min

Determines whole chromosomal gains and losses. Chromosome should contain no transitions, have its absolute median equal or greater than medChrom.min and at least medChrom.min has to be greater or less than 0.

Value

num.transitions

matrix of dimensions maxChrom by number of samples. It contains number of transitions that were recorded on a given chromosome for a given sample.

num.amplifications

matrix of dimensions maxChrom by number of samples It contains number of amplifications that were recorded on a given chromosome for a given sample.

num.aberrations

matrix of dimensions maxChrom by number of samples. It contains number of focal aberrations that were recorded on a given chromosome for a given sample.

num.outliers

matrix of dimensions maxChrom by number of samples. It contains number of outliers that were recorded on a given chromosome for a given sample.

num.transitions.binary

binary matrix of dimensions maxChrom by number of samples. Non-zero entry indicates whether 1 or more transitions were recorded on a given chromosome for a given sample.

num.amplifications.binary

binary matrix of dimensions maxChrom by number of samples. Non-zero entry indicates whether 1 or more amplifications were recorded on a given chromosome for a given sample.

num.aberrations.binary

binary matrix of dimensions maxChrom by number of samples. Non-zero entry indicates whether 1 or more focal aberrations were recorded on a given chromosome for a given sample.

num.outliers.binary

binary matrix of dimensions maxChrom by number of samples. Non-zero entry indicates whether 1 or more outliers were recorded on a given chromosome for a given sample.

whole.chrom.gain.loss

matrix of dimensions maxChrom by number of samples. Positive entry indicates that a given chromosome was gained in a given sample, negative entry indicates that a given chromosome was lost in a given sample, 0 entry is normal chromosome and NA marks chromosomes with one or more transition.

size.amplicons

matrix of dimensions maxChrom by number of samples. Reports size of a given chromosome that is amplified (kb units) in a given sample.

num.amplicons

matrix of dimensions maxChrom by number of samples. Reports number of disjoint amplicons on a given chromosome for a given sample.

outliers

list containing 3 matrices of dimensions number of clones by number of samples. See findOutliers.func.

aberrations

list containing a matrix of dimensions number of clones by number of samples. See findAber.func.

transitions

list containing 2 matrices of dimensions number of clones by number of samples. See findTrans.func.

amplifications

list containing a matrix of dimensions number of clones by number of samples. See findAmplif.func.

Details

The default parameters generally work. Threshold for merging may be changed depending on the expected normal cell contamination and/or expected magnitude of the changes. AIC model generally works, however, may need to be readjusted depending on how liberal or conservative one wants to be in finding genomic events. We recommend BIC criterion with delta = 1 for noisier data.

See Also

aCGH find.hmm.states mergeFunc findAber.func findTrans.func findAmplif.func findOutliers.func