Hi everyone, wanted to run my open chromatin mapping methodology with DiffBind by you and see if there is room for improvement. Basically have 3-4 replicates per experiment where the vast majority of underlying peaks will be shared between groups. In the sampleSheet just have the BAMs and narrowPeak files from the macs2 output, and using CONDITION as the contrast. Comes from PE 75 NextSeq high output runs.
Running the following:
samples <- read.csv(file.path(system.file("extra", package="DiffBind"),"RPMG_DNAse.csv"))
RPMG<- dba(minOverlap = 2, sampleSheet = "RPMG_DNAse.csv", peakCaller = "macs", peakFormat = "narrow", config=data.frame(AnalysisMethod=DBA_EDGER, fragmentSize=151))
RPMG <- dba.count(RPMG, summits=250)
RPMG<- dba.contrast(RPMG, categories=DBA_CONDITION)
RPMG.DB <- dba.report(RPMG)
Basically noticed that I am getting slightly more peaks using EdgeR than DeSeq2 however still very few Diff peaks given a consensus peak set of over 90K. Wondering everyones thoughts, thanks!