How to calculate differential methylation from nanopore reads?
I have 2 timepoint-specific conditions (t=0 and t=X) and 12 specimens. I used nanopolish to calculate methylation signatures per base, in particular, with this script: https://github.com/jts/nanopolish/blob/master/scripts/calculate_methylation_frequency.py
The output generated looks like the following:
where methylated_frequency ranges from floating point values within the range [0,1] (e.g. 0.0, 0.382, 0.618, 1.0)
Are there anyways I can use this data to calculate differential methylation between my groups?
For example, maybe methylation events in region [x-y] are differentially methylated in t=X compared to t=0 or vice versa.
1 answer
I'd suggest looking at pycoMeth.
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Hi O.rka, I'm in a similar situation...what did you end up using?
I second @WouterDeCoste in using pycoMeth. I made a pipeline figure for the project in this question. I hope it helps out.
https://drive.google.com/drive/folders/1vVZ78sgf60Fqd-6Hb4TrG-0-yxUm6ak_?usp=sharing
There are 4 pdfs, one per step and one with them merged.
Also, I recommend using f5c over nanopolish (same output format just way faster) but PLEASE don't forget to use
--meth-out-version 2(this is why https://github.com/a-slide/pycoMeth/issues/49#issuecomment-766195520). It will save you a lot of time and frustration in the future. Basically, it's only compatible w/ pycoMeth if you use that format.