Comments (11)
Thanks for your interest.
I'd love to make epic usable on less common builds/genomes, as I know that is a pain point with many other callers.
All you need is a file with the chromosome/unplaced contig names in one column and the sizes in another.
For UCSC this might look like:
chr1 248956422
chr2 242193529
chr3 198295559
chr4 190214555
chr5 181538259
chr6 170805979
chr7 159345973
chrX 156040895
chr8 145138636
chr9 138394717
Then you can invoke epic with -cs <chromsizes_file>
and set the -egf
to a number like 0.8. Just setting the egf to any number will only affect the number of regions considered enriched, it will not find different regions or affect the rank order of the results. So if you are interested in the top 1k scoring regions this will work.
The egf suggestion is just a hack until I am able to get the egf info which is computationally expensive. Do you have a link to a fasta genome of your organism?
Endre
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Also, do you have input/background files? epic needs that to run - just telling you upfront so you do not waste your time :)
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But epic should be pretty fast. If it has been running for a long time there is something strange going on :/
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Hmm, usual genomes have ~25 chromosomes, with your contigs you have 232155. This might be why it takes so long. Is it possible to only run it on the canonical chromosomes?
I will think more about it, I promise.
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Related Issues (20)
- No Releases HOT 2
- epic 0.2.9 compute_score_threshold.py:24 RuntimeWarning: divide by zero encountered in log HOT 6
- run epic without control samples HOT 2
- Best choice parameters HOT 1
- epic-merge throws an error of ValueError: Cannot convert NA to integer HOT 3
- epic and conda HOT 2
- trackline and recommanded parameters HOT 9
- problem with output HOT 10
- cannot recognize genome HOT 5
- conda still installs 0.2.9 HOT 10
- are read ids necessary in SE mode? HOT 1
- calculating memory requirements based on bam file size HOT 7
- Epic effective for HOT 11
- How does EPIC work ? HOT 6
- Epic depricated HOT 1
- Epic-effective: TypeError: cannot concatenate 'str' and 'NoneType' objects HOT 5
- Genomes cannot find
- ChIP-seq WT vs mutants comparison HOT 2
- Arabidopsis thaliana HOT 2
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