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2 hours ago by


I have two cell lines (clones derived from patient with mutation; mutation was rescued in one cell line but not the other) with ChIP, ATAC, and RNA-Seq in each -- and I want to compare them. The differential analysis yielded lots of pathways like "Chr9p13" and "Amplicon Chr6q22 in Breast Cancer", which lead to us to consider that there might be CNVs between these cell lines. We did a high-coverage WGS run to confirm this -- we ended up finding large-scale copy number changes between them.

Now that I know what the copy number changes are, I am wondering if anyone is aware of tools/approaches to using that information in re-analyzing our ChIP, ATAC, and RNA Seq data?

This was the approach I was considering at first: (1) Normalizing the ChIP and ATAC Seq by using the WGS as the Input for peak calling OR (1) Take the results from something like DiffBind and weighing the fold change and p value for differential peaks in CNV regions by simply dividing the -log10(pVal) and fold change by the copy fold change at the location and (2) Maybe don't normalize the RNA-Seq by CNV because the CNVs lead to biologically-meaningful transcriptomic differences

Thank you for your time,
Henry Miller


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2 hours ago


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