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Normalization and differential analysis in ATAC-seq data
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19 months ago
anais1396 • 20
Brussels

Hello everyone!

I would like to know if someone had experiences with normalization and differential expression on ATAC-seq data. After using MACS2 for the peak calling, how can we use Dseq2 or EdgeR on these datas? Someone try this? What is the protocol you use to do that?

Thank you in advance!

Anaïs

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I believe you could use diffBind strategy: merge the peaks of different samples, count the number of reads in it and perform a differential analysis on those counts. I don't however have experience on ATAC-seq myself, so I cannot guarantee that's the best approach.

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When we do this we first we filter our samples so that we are only using samples with at least 35M read ends and at least 10% FRiP (fraction reads in peaks). We then downsample each sample so that all samples have the same number of reads, before merging all samples and calling peaks. This becomes our feature set. We then count the number of read ends in each feature for our non-down sampled samples and use DESeq2 standard normalisation and differential calling to find differential peaks. We use a more stringent differential expression FDR value than you would nrormally use. I think this is conceptually similar to the diffBind approach. Eyeballing the results, it seems to work pretty well, but we don't yet have any molecular validation of the results.

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