estimateExonGenewiseDisp {edgeR} | R Documentation

## Estimate Genewise Dispersions from Exon-Level Count Data

### Description

Estimate a dispersion value for each gene from exon-level count data by collapsing exons into the genes to which they belong.

### Usage

    estimateExonGenewiseDisp(y, geneID, group=NULL)

### Arguments

`y` | either a matrix of exon-level counts or a `DGEList` object with (at least) elements `counts` (table of counts summarized at the exon level) and `samples` (data frame containing information about experimental group, library size and normalization factor for the library size). Each row of `y` should represent one exon.
`geneID` | vector of length equal to the number of rows of `y`, which provides the gene identifier for each exon in `y`. These identifiers are used to group the relevant exons into genes for the gene-level analysis of splice variation.
`group` | factor supplying the experimental group/condition to which each sample (column of `y`) belongs. If `NULL` (default) the function will try to extract if from `y`, which only works if `y` is a `DGEList` object.

### Details

This function can be used to compute genewise dispersion estimates (for an experiment with a one-way, or multiple group, layout) from exon-level count data. `estimateCommonDisp` and `estimateTagwiseDisp` are used to do the computation and estimation, and the default arguments for those functions are used.

### Value

`estimateExonGenewiseDisp` returns a vector of genewise dispersion estimates, one for each unique `geneID`.

### Author(s)

Davis McCarthy, Gordon Smyth

### See Also

`estimateCommonDisp` and related functions for estimating the dispersion parameter for the negative binomial model.

### Examples

    # generate exon counts from NB, create list object
    y<-matrix(rnbinom(40,size=1,mu=10),nrow=10)
    d<-DGEList(counts=y,group=rep(1:2,each=2))
    genes <- rep(c("gene.1","gene.2"), each=5)
    estimateExonGenewiseDisp(d, genes)

[Package edgeR version 3.34.1 Index]