DBAnalyze: Performs differential binding analysis
In CSSQ: Chip-seq Signal Quantifier Pipeline

Description Usage Arguments Value Examples

This is a wrapper function that performs the different parts of differential binding analysis. Returns a GRanges-class with a calculated P-value and Fold change for each region.

1	DBAnalyze(preprocessedData, comparison)

`preprocessedData`	A `RangedSummarizedExperiment-class` object from `preprocessData`.
`comparison`	A vector containing the comparison to be made. Names here need to correspond to the sample groups in the sample file (Eg. c("G1",G2") means the comparison G1/G2).

A GRanges-class object containing the regions along with their P-values and Fold change for the comparison.

exRange <- GRanges(seqnames=c("chr1","chr2","chr3","chr4"),
ranges=IRanges(start=c(1000,2000,3000,4000),end=c(1500,2500,3500,4500)))
sampleInfo <- read.table(system.file("extdata", "sample_info.txt", 
package="CSSQ",mustWork = TRUE),sep="\t",header=TRUE)
exCount <- matrix(c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16),nrow=4,ncol=4)
exData <- SummarizedExperiment(assays = list(ansCount=exCount),
rowRanges=exRange,colData=sampleInfo)
normExData <- normalizeData(exData,numClusters=2)
res <- DBAnalyze(normExData,comparison=c("HSMM","HESC"))
res