Running on large dataset about pirate HOT 2 CLOSED

Hi Nicolas,

Thanks for using it!

PIRATE has been successfully used on very large datasets >25,000 genomes. I would suggest that you:

1/ Check the genomes for quality. One poor quality genome can have a detrimental effect on the clustering and especially the paralog identification and classification.
2/ Start with a much smaller subset of your most diverse samples so that you can pick a range of thresholds (--steps) that accurately captures the diversity in your collection. You could also experiment with inflation values here to ensure sensible clusters are produced. I am afraid I don't have any tips for selecting an MCL inflat value for you :(
3/ Don't run it with gene alignment, it will take ages to finish and can be run separately or on genes of interest afterwards.
4/ You can also run it with paralog detection off (--para-off) on the initial run as this can take a long time to complete. It can then be rerun with paralog detection only, using the --pan-off option, once it has finished clustering at least once. You WILL need to keep intermediate files on each run for this to work (-z 2). I would test the workflow on a smaller subset so that you don't put the wrong options in on your full set and remove intermediate files or have to reprocess everything :)
5/ Throw as many cores as you can at it.

I hope that helps,
S

from pirate.

Hi Sion

Thanks for the quick input! I will let you know how it will work for me

from pirate.