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Agora-generic pipeline seems to be “stuck” for several days after adding 1 more genome #29
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Hi maxnest, It's probably due to the fact that there are very few ancestral genes in this category for one ancestor after adding the new species. grep "conserved pairs for" pairwise/pairs-size-1.0-1.0/log On the data before the insertion of the new genome and after the insertion? you can contact me directly at alouis@bio.ens.psl.eu if you want. |
Hi @alouis72 and colleagues, Thanks for the great tool! I also got the same problem with my dataset, but instead that the problem appeared after adding one more genome, I couldn't run the generic pipeline in the first place (but works for the basic). I wonder what is the problem and whether you could help solving it. Thank you! |
Hi diekei, Maybe the thing to do, is to try generic pipeline only on specific ancestors (with option -target= ) and loop. for sizeParams in [(1.0,1.0), (0.9,1.1), (0.77,1.33)]: Hope this will work, |
Hi @alouis72, Many thanks for the super swift response! and the two possible suggestions. Thank you!! |
Dear colleagues,
Thank you for your useful and important approach! Unfortunately, I have some issues with ‘agora-generic’ pipeline. Previously, I have gotten good results when analyzing data using this pipeline. To improve the results, I added one new genome and after 6 completed tasks (Status: 49 to do, 1 running, 6 done, 0 failed -- 56 total) the program seems to be “stuck” for several days. Restarting the pipeline and running the analysis on another computer did not help. It is worth noting that, firstly, previously the pipeline successfully completed the analysis after a few minutes, secondly, table of processes indicates that Python-related processes are still running, thirdly, when analyzing the same data set using ‘basic’ and ‘plants’ pipeline, all processes are completed successfully in a few minutes. Given that the ‘generic’ pipeline tries to find the best parameters for each ancestral node of the phylogenetic tree, is such a long data processing time expected or not? Have you noticed this before? And what can you recommend?
I would be grateful for any help,
Thank you very much!
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