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Differential ChIP-Seq Analysis

Hello everyone, I have ChIP-Seq datasets. With Bowtie2, now I have BAM files. I mostly use SeqMonk for these kind of analyses but I do not think it does not have a tool for differential ChIP-Seq analysis. I used MACS for peak calling (on SeqMonk) and I have values too.

1) Anyone knows a suitable and fast (Windows 10 would be awesome) tool for this analysis?

2) Does a basic statistical analysis (like t-test) to the log2 peak values of each sample work?

3) Do DESeq2 or EdgeR to the raw counts work?

Thank you.

chip-seq r next-gen alignment
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updated by igor igor • written by hkarakurt hkarakurt

3 answers

You should check this paper for a comprehensive overview of the various differential binding tools: https://doi.org/10.1093/bib/bbv110

Here, we have reviewed 14 tools, which have been developed to determine differential enrichment between two conditions. They differ in their algorithmic setups, and also in the range of applicability. Hence, we have benchmarked these tools on real data sets for transcription factors and histone modifications, as well as on simulated data sets to quantitatively evaluate their performance. Overall, there is a great variety in the type of signal detected by these tools with a surprisingly low level of agreement. Depending on the type of analysis performed, the choice of method will crucially impact the outcome.

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written by igor igor

Yes - for a particular set of peaks, you can quantify counts (with htseq-count, featureCounts, etc.) and then use DESeq2/edgeR for p-value calculations.

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written by Charles Warden Charles Warden

Look into deepTools bigWigCompare for comparing bigWig files based on the gene mapping

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written by Hussain Ather Hussain Ather

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