Comments (4)
It's related to a better way to control the threshold of calling peaks. One way is to use the IDR approach if you have multiple replicates. Or if you have one deeply sequenced sample, you can divide them into multiple technical replicates, then use the IDR approach later ( it's called pseudo replicate in the ENCODE pipeline, for example encode Histone ChIP-seq pipeline ). Another way is to try to use the cutoff-analysis approach to decide a better cutoff in MACS.
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Thank you for your reply @taoliu! Digging deeper into my dataset, I realized that these problematic samples have noticeably higher proportion of peaks with low signalValue (but with high confidence).
I tried running the cutoff analysis and found that even using a very stringent qvlaue couldn't get rid of these weak peaks. My question now is, would you recommend using signalValue threshold? The same antibody was used for all samples and processed together, so I don't think it's the problem with the reagent. Many thanks again.
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@SplitInf Yes. I would suggest you apply two thresholds -- signalValue (it is the log2foldchange values, so 1 means 2 folds), and p or q-value. It's common that when the number is big, a small log2fc can have a high confidence (p or q-value). As in RNA-seq differentially expressed genes analysis (e.g. volcano plot), you can use both at the same time to narrow down the results.
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Related Issues (20)
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