posteriorProbability {crlmm} | R Documentation

## Calculate the posterior probability for integer copy numbers.

### Description

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

### Usage

    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

    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)

[Package crlmm version 1.40.0 Index]