I found the solution to my previous questions. However, now I am comparing the results from the available edgeR analysis with the robust edgeR pipeline with QL method based on raw read counts. This is the pipeline that I want to use. I found the raw read counts by
reads.5 = dba.count(prol.5, peaks=NULL, score=DBA_SCORE_READS) bindingMatrix.5 = dba.peakset(reads.5, bRetrieve=TRUE, DataType=DBA_DATA_FRAME)
However, these counts are different from:
de.5.edger = dba.analyze(contrast.5, method=DBA_EDGER, bFullLibrarySize=FALSE, bTagwise=TRUE, bReduceObjects=FALSE) names(de.5.edger) de.5.edger$contrasts de.5.edger$contrasts[]$edgeR$counts[1:5,]
and as a result, I also get totally different DE genes.
How do I get the same counts with the dba.count function?