estimateDispersion {deepSNV} | R Documentation

## Estimate the Dispersion factor in a beta-binomial model.

### Description

This function estimates the dispersion factor in a beta-binomial model of the nucleotide counts. This model assumes that the count for nucleotide j at position i is distributed after a beta-binomial X_ib ~ BB(n_i; alpha, beta_ij), where n_i is the coverage. The base and nucleotide specific parameter beta_ij is estimated from the local mean by the method-of-moments estimate, alpha is a shared overdispersion parameter. It is estimated via a numerical optimization of the likelihood under the null-hypothesis.

### Usage

    estimateDispersion(test, control, ...)

    ## S4 method for signature 'deepSNV,missing'
    estimateDispersion(test, control, alternative = NULL, interval = c(0,1000))

    ## S4 method for signature 'matrix,matrix'
    estimateDispersion(test, control, alternative = NULL, interval = c(0,1000))

### Arguments

`test` | Either a deepSNV object, or a matrix with the test counts.
`control` | Missing if test is a deepSNV object, otherwise missing.
`...` | Additional param passed to specific methods
`alternative` | The alternative to be tested. One of "greater", "less", "two-sided" (default). If test is a deepSNV object, automatically taken from the corresponding slot if unspecified.
`interval` | The interval to be screened for the overdispersion factor. Default (0,1000).

### Value

A `deepSNV-class` object if the input was a deepSNV object. Otherwise the loglikelihood and the estimated parameter.

### Author(s)

Moritz Gerstung

### Examples

    data("RCC", package="deepSNV")
    plot(RCC)
    summary(RCC)[,1:6]
    RCC.bb = estimateDispersion(RCC, alternative = "two.sided")
    summary(RCC.bb)

[Package deepSNV version 1.33.3 Index]