topSplice: Top table of differentially spliced genes or exons

In limma: Linear Models for Microarray Data

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

limma documentation built on Nov. 8, 2020, 8:28 p.m.