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Out of memory error #4
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Due to the problem of multi-threading in Python, part of the parallel calculation is handled by multi-processes, and all data in the memory will be replicated in each process. Please try to run PEPPA with fewer processes (i.e., 4). I will close this issue for now but please re-open it if you still get an out-of-memory problem. |
Dear Zhemin, Thank you for your suggestion, I will try this. Best wishes, |
Dear Zhemin, I tried to run with fewer threads, as you suggested, even down to a single thread. Unfortunately, the issue remained. In annex the log file with the error - it seems to occur in the BLASTn step. Best wishes, |
I have pushed PEPPA in pypi with a formal version number 1.0 |
Hi Zhemin, I installed PEPPA version 1.0 using pip, as you suggested. It didn't fix the problem: I still got out-of-memory errors, no matter the number of threads I used. However, I took a closer look at how PEPPA works, and it seems to me that it is not suited for datasets above the genus level? While I have a genome dataset on the order level; I think the blastn searches are not sensitive enough for those. When I set I have one additional remark: I found a bug in PEPPA_parser.py. In line 64, there is a Best regards, |
Thank you for the bug report (again) and the solution you found. PEPPA allows a lower limit of "--match_identity" down to 0.4, so your value of 0.5 is fine. However, the "clust_identity" and "clust_match_prop" values are certainly out of my testing scope. I think the phylogeny based paralog splitting will still be able to handle this but am not for sure. Will push up the fixation for the bug in PEPPA_parser.py later this week. |
Dear Zhemin,
Thank you for making PEPPA publicly available and for putting the publication on bioRxiv, it's a very nice read!
I managed to install PEPPA successfully and tried to do a test run on 73 genomes of the order Lactobacillales. After a few minutes I got an out of memory error (memory was indeed full) and the job aborted. Is there anything I can do to solve this? I have 16GB of memory and was using all 16 threads I have available.
Best wishes,
Stijn
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