catchSalmon: Process Kallisto or Salmon Output

In edgeR: Empirical Analysis of Digital Gene Expression Data in R

Description

Read transcriptwise counts from kallisto or Salmon output for a series of samples and use the bootstrap samples to estimate the mapping uncertainty for each transcript.

Usage

catchKallisto(paths, verbose = TRUE)
catchSalmon(paths, verbose = TRUE)

Arguments

paths	character vector giving paths to the directories created by kallisto.
verbose	logical. If TRUE, summary information is printed as each sample is catch.

Details

These functions assume that kallisto or Salmon have been run to obtain estimated transcript counts for one or more RNA samples, and that bootstrap samples have also been generated. These functions catch the counts and use the bootstrap samples to estimate an over-dispersion coefficient for each transcript. Transcripts that overlap other transcripts and have greater read mapping uncertaintly will have greater over-dispersion coefficients.

The data is then ready for analysis in edgeR.

Value

A list containing components

counts	matrix of transcript counts
annotation	data.frame of transcript information.

Author(s)

Gordon Smyth

Examples

## Not run: 
s <- catchSalmon(paths)
dge <- DGEList(counts=s$counts/s$annotation$Overdispersion, genes=s$annotation)

## End(Not run)

edgeR documentation built on Jan. 16, 2021, 2:03 a.m.