posteriorProbability: Calculate the posterior probability for integer copy numbers.

Description Usage Arguments Details Value Note Author(s) See Also Examples

Description

Calculate the posterior probability for integer copy numbers using the bivariate normal prediction regions.

Usage

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posteriorProbability(object, predictRegion, copyNumber = 0:4, w)

Arguments

object

A CNSet object.

predictRegion

A list containing the bivariate normal prediction region for each of the possible genotypes.

copyNumber

Integer vector.

w

numeric vector of prior probabilities for each of the copy number states. Must be the same length as copyNumber and sum to 1.

Details

This is currently under development.

Value

An array (features x samples x copy number)

Note

This is under development. Use at your own risk.

Author(s)

R. Scharpf

See Also

predictionRegion, genotypes

Examples

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data(cnSetExample)
pr <- predictionRegion(cnSetExample, copyNumber=0:4)
pp <- posteriorProbability(cnSetExample, predictRegion=pr)
dim(pp)

## multiple batches
data(cnSetExample2)
pr <- predictionRegion(cnSetExample2, copyNumber=0:4)
pp <- posteriorProbability(cnSetExample2, predictRegion=pr)

benilton/crlmm documentation built on Dec. 27, 2019, 12:12 a.m.