Differential gene expression and differential bin/junction usage estimation

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Description

Estimate differential expression at gene level and differential usage at bin and junction level.

Usage

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DUreport(counts, targets, pair, group, minGenReads, minBinReads, minRds,ignoreExternal,threshold)

Arguments

counts

An object of class ASpliCounts

targets

A dataframe containing sample, bam and condition columns

pair

vector of length two, either numeric or character, providing the pair of groups to be compared

group

Factorial vector with tags for each sample

minGenReads

Default 10 reads

minBinReads

Default 5 reads

minRds

Default 0.05

ignoreExternal

Ignore Exon Bins at the beggining or end of the transcript. Default TRUE

threshold

Minimun number of junction. Default 5

Value

An ASpliDU object with results at genes, bins and junctions level

Author(s)

Estefania Mancini, Marcelo Yanovsky, Ariel Chernomoretz

See Also

DEXSeq, edgeR Accesors: genesDE, binsDU,junctionsDU Export: writeDU

Examples

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library(RNAseqData.HNRNPC.bam.chr14)
chr14 <- system.file("extdata","chr14.sqlite", package="ASpli")
genome <- loadDb(chr14)
features <- binGenome(genome)
targets <- data.frame(bam=RNAseqData.HNRNPC.bam.chr14_BAMFILES,
                       condition=c(rep("CT",4),rep("KD",4)))
bam <- loadBAM(targets)
counts <- readCounts(features, bam, l=100L, maxISize=50000)
group <- factor(c(rep("CT",4), 
                rep("KD",4)))
pair <- c("CT","KD")  
du <- DUreport(counts, targets, pair, group)
writeDU(du, output.dir="only_du")