Hi clipseq team, i'd like to start doing analysis ...
# clipseq
ž
Hi clipseq team, i'd like to start doing analysis of CLIP data for transposons and was hoping maybe I could pick someone's brain on where to start with the pipeline. So far I noticed if I try to get signal over multimapping regions this doesn't work, and if I build a custom fasta with masked regions but additional consensus sequences this works but then crosslink sites don't get reported by most peakcallers but icount (because there is no defined biotype for these i assume). Really appreciate any insight into this and any messy workarounds that I could test and see how peaks will behave on transposons. Thanks a lot!
c
Hi Žiga - if you use the pipeline run on app.flow.bio it outputs a multimapped bam that you could then analyse further, but if you're doing that you might aswell just write your own pipeline. It's something we're working on but can't tell you when it will be completed. Infact, if you work out something nice we could help you to contribute it to the nfcore pipeline
Peak callers like paraclu and clippy are quite annotation-agnostic so might be better for your consensus situation
you could also try gene yeo's skipper pipeline - their approach is to first map to everything in repbase, then they summarise and calculate enriched regions
i think you will lose some info on position of elements within genes, that you may or may not care about, but you could get a better idea of that from summarising the multimapped genome alignment in parallel
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ž
That's already some great insight Charlotte, thanks a lot! I'll come back if I find time to really dig into it and no existing pipeline works well enough for me, but looking forward for what you experts come up with as well 🙂
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