topSplice {limma} | R Documentation

## Top table of differentially spliced genes or exons

### Description

Top table ranking the most differentially spliced genes or exons.

### Usage

    topSplice(fit, coef = ncol(fit), test = "simes", number = 10, FDR=1, sort.by = "p")

### Arguments

`fit` | `MArrayLM` fit object produced by `diffSplice`.
`coef` | the coefficient (column) of fit for which differentially splicing is assessed.
`test` | character string specifying which statistical test to apply. Possible values are `"simes"`, `"F"` or `"t"`. `"F"` gives F-tests for each gene. `"t"` gives t-tests for each exon. `"simes"` gives genewise p-values derived from the t-tests after Simes adjustment for each gene.
`number` | integer, maximum number of rows to output.
`FDR` | numeric, only show exons or genes with false discovery rate less than this cutoff.
`sort.by` | character string specifying which column to sort results by. Possible values for `"p"`, `"logFC"`, `"NExons"` or `"none"`. `"logFC"` is only available if `test="t"` and `"NExons"` is only available if `test="simes"` or `test="F"`.

### Details

Ranks genes or exons by evidence for differential splicing. The F-statistic tests for any differences in exon usage between experimental conditions. The exon-level t-statistics test for differences between each exon and all other exons for the same gene.

The Simes processes the exon-level p-values to give an overall call of differential splicing for each gene. It returns the minimum Simes-adjusted p-values for each gene.

The F-tests are likely to be powerful for genes in which several exons are differentially splices. The Simes p-values is likely to be more powerful when only a minority of the exons for a gene are differentially spliced. The exon-level t-tests are not recommended for formal error rate control.

### Value

A data.frame with any annotation columns found in `fit` plus the following columns

`logFC` | log2-fold change of exon vs other exons for the same gene (if `level="exon"`)
`t` | moderated t-statistic (if `level="exon"`)
`F` | moderated F-statistic (if `level="gene"`)
`P.Value` | p-value
`FDR` | false discovery rate

### Author(s)

Gordon Smyth

### See Also

`diffSplice`, `plotSplice`

A summary of functions available in LIMMA for RNA-seq analysis is given in 11.RNAseq.

### Examples

    # See diffSplice

[Package limma version 3.42.2 Index]