assess.CNA: Significance assessment of copy number alterations

In ioncopy: Calling Copy Number Alterations in Amplicon Sequencing Data

Description

Starting from a matrix of coverages, the corresponding matrix of copy numbers is calculated. A null model for significance assessment of copy number alterations is fitted. Each amplicon in each sample is assessed for significance. Summarized copy numbers and p-values for genes are calculated as descibed below.

Usage

assess.CNA(coverage.target, coverage.source=NULL, method.pooled="amplicon", thres.cov=100)

Arguments

coverage.target	A numeric matrix containing the target coverages of each amplicon (rows) in each sample (columns). The target data are investigated for copy number alterations.
coverage.source	A numeric matrix containing the source coverages of each amplicon (rows) in each sample (columns). The source data are used to fit a null model. If NULL, the target data are used to fit the null model.
method.pooled	Method used for the estimation of the null model. Either one common null model for all amplicons (pooled) or individual null models for each of the amplicons (amplicon) are fitted.
thres.cov	Theshold for the minimal mean coverage of an amplicon to be included in the analysis.

Value

List containing the following elements: Matrix of copy numbers with the estimated null model ("model"), estimates of copy numbers ("CN.a" and "CN.g") for amplicons and genes as well as p-values of copy number alterations ("P.a" and "P.g") for amplicons and genes. Copy numbers for genes are calculated as average of the copy numbers of all amplicons interrogating the gene, p-values for genes are calculated using Fisher's method.

Examples

## Not run: 
data(coverage)
CNA <- assess.CNA(coverage)

## End(Not run)

ioncopy documentation built on Aug. 11, 2020, 5:08 p.m.