DUreport_DEXSeq: Differential gene expression and differential bin/junction...

In estepi/ASpliD: Analysis of alternative splicing using RNA-Seq

Description

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

Usage

DUreport_DEXSeq(counts, targets, pair, group, minGenReads, minBinReads, minRds,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
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

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_DEXSeq(counts, targets, pair, group)
writeDU(du, output.dir="only_du")

estepi/ASpliD documentation built on May 16, 2019, 8:53 a.m.