Closed BenjaminSchwessinger closed 4 years ago
a-slide
commented
4 years ago Hi @BenjaminSchwessinger, I have a section describing the header of each tool in he documentation:
Did you mean you'd like more than that ?
Cheers
BenjaminSchwessinger
commented
4 years ago Hi,
I missed this page. Apologies for this. Looks pretty comprehensive.
Now I still have some questions:
https://a-slide.github.io/pycoMeth/CpG_Aggregate/usage/
In the TSV section:
median_llr: Median of log likelihood ratios for all read mapped <- maybe explain your cut-offs for methy/unmeth like below for beds.
https://a-slide.github.io/pycoMeth/Meth_Comp/usage/
In TSV section:
neg_med / pos_med / ambiguous_med: Number of samples with a median below the negative llr threshold / above the positive llr threshold or with and ambiguous median between the 2 thresholds <- might be worth spelling out the thresholds again (>2 and <-2).
Thanks!
Great tool.
Benjamin
On 31/3/20 7:45 pm, Adrien Leger wrote:
Hi @BenjaminSchwessingerhttps://github.com/BenjaminSchwessinger, I have a section describing the header of each tool in he documentation:
Did you mean you'd like more than that ?
Cheers
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Benjamin Schwessinger PhD. ARC Future Fellow 2018 Senior Lecturer Division of Plant Science Research School of Biology College of Science Linnaeus Building (134), Linnaeus Way The Australian National University Canberra ACT 0200 Australia
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a-slide
commented
4 years ago Hi @BenjaminSchwessinger,
I slightly updated the doc in the last version of PycoMeth
Regarding CpG_Aggregate usage, there is no cuttoff for the median, it is just the median of all observed llr for the position
As for Meth_Comp usage, the default threshold is indeed 2 (like in Nanopolish) but it can actually be redefined by users with min_diff_llr.
The last version can generate HTML reports of the significant candidates.
Cheers
Ad
Hi, Nice tool and I think I wrapped my head round it. Is there a chance to describe the outputfiles a bit more e.g. llr and such. I can guess what it all means and some clear explanation and docs will go a long way towards knowing.
Thanks!
Benjamin