I have data for 3 histone marks (2 for silencing and 1 for activation) each mark has three replicates. when I run the diffBind package I have three contrast:

Silence1-Activation Silence1-Silence2 Silence2-Activation

When I run dba.plotBox for any of contrasts I will have the same distribution of reads.like below:

I even tried to start with 1000 peaks of each one that showed higher fold change but again got the same pattern for plotbox. Even the outliers are the same, How it's possible?

here is the code:

peaks10kthreemarksobj <- dba(sampleSheet="samplesheets10kPeaks.csv") peaks10kthreemarksobj <- dba.count(peaks10kthreemarksobj, bUseSummarizeOverlaps=TRUE,bParallel=TRUE) peaks10kthreemarksobj <- dba.contrast(peaks10kthreemarksobj, categories=DBAFACTOR) peaks10kthreemarksobj <- dba.analyze(peaks10kthreemarksobj, method=DBAALLMETHODS, bParallel=T) dba.plotBox(peaks10kthreemarksobj, contrast=3)

The issue is your SampleIDs. They must all be unique. I've updated the documentation to reflect this.

You should fix this in your sample sheet and re-run the analysis. Alternatively, you can re-set the SampleIDs directly in the DBA object:

peaks_10k_threemarks_obj$class[DBA_ID,] <- 1:9 #vector of unique sample IDs
dba.plotBox(peaks_10k_threemarks_obj, contrast=3)

It would help to see your sample sheet.

If you send me a copy of peaks10kthreemarksobj (either after dba.count() or dba.analyze()) I can have a look and give you a better answer as to what is going on.

As cross-posted in Biostars, the issue was that the SampleIDs need to be unique. Documentation will be updated to make this clear.

As cross-posted in Biostars, the issue was that the SampleIDs need to be unique. Documentation will be updated to make this clear.