Hello,

I have ATAC sequencing data for two types of cells, each with three replicates. Get strange results by DiffBind analysis. Why is my volcano map only halfway？ I don't know where I went wrong. Is there a problem with the original data or with the processing results? Can anyone answer it. here is my SampleSheet.

last.BAM was compared to the genome.Mitochondrial duplication, PCR duplication and low-quality reads were removed. Paired-ended sequencing to the same chromosome

figure2

figure3

figure4

figure5

here is my code

       a <- dba(sampleSheet="diff.csv")
       a <- dba.count(a,bUseSummarizeOverlaps = TRUE)

#warning:In serialize(data, node$con) :
 #'package:stats' may not be available when loading


       dba.plotPCA(a,attributes=DBA_FACTOR,label=DBA_ID)
#figure2

       plot(a)
#figure3

       a <- dba.contrast(a,categories = DBA_FACTOR,minMembers = 2)
       a <- dba.analyze(a,method=DBA_DESEQ2)
#warning: solve(): system is singular (rcond: 3.89123e-18); attempting approx solution

       dba.show(a,bContrasts = T)
#  Factor Group Samples Group2 Samples2 DB.DESeq2
# 1 Factor    ab       3     aa        3         8

       dba.plotMA(a)
#warning:In KernSmooth::bkde2D(x, bandwidth = bandwidth, gridsize = nbin,  :Binning grid too coarse for current (small) bandwidth: consider increasing 'gridsize'

#figure4

#This picture is weird.

       dba.plotVolcano(a)

#figure5



sessionInfo( )

This is showing that all of the open chromatin changes are in the same "direction": sites that are open in the aa condition only. There are no sites open in ab that are not also open in aa, so the MA and volcano plots are highly asymmetric.

There are many biological conditions that lead to these types of asymmetric differences. Given how few sites there are, I'd suggest looking at them in a genome browser to see if the sequencing data show the gain in open chromatin in aa at these sites.