stat.limma {metaseqR} | R Documentation

## Statistical testing with limma

### Description

This function is a wrapper over limma statistical testing. It accepts a matrix of normalized gene counts or an S4 object specific to each normalization algorithm supported by metaseqR.

### Usage

        stat.limma(object, sample.list, contrast.list = NULL,
            stat.args = NULL)

### Arguments

`object` | a matrix or an object specific to each normalization algorithm supported by metaseqR, containing normalized counts. Apart from matrix (also for NOISeq), the object can be a SeqExpressionSet (EDASeq), CountDataSet (DESeq) or DGEList (edgeR).
`sample.list` | the list containing condition names and the samples under each condition.
`contrast.list` | a named structured list of contrasts as returned by `make.contrast.list` or just the vector of contrasts as defined in the main help page of `metaseqr`.
`stat.args` | a list of edgeR statistical algorithm parameters. See the result of `get.defaults("statistics",` `"limma")` for an example and how you can modify it.

### Value

A named list of p-values, whose names are the names of the contrasts.

### Author(s)

Panagiotis Moulos

### Examples

    require(DESeq)
    data.matrix <- counts(makeExampleCountDataSet())
    sample.list <- list(A=c("A1","A2"),B=c("B1","B2","B3"))
    contrast <- "A_vs_B"
    norm.data.matrix <- normalize.edger(data.matrix,sample.list)
    p <- stat.limma(norm.data.matrix,sample.list,contrast)

[Package metaseqR version 1.27.13 Index]