Is long computation time in humann3 related to not using knead data?

Microbial community profiling HUMAnN
1

Greetings,
I am running 150 bp PE metagenomic reads from soil samples on a university HPC cluster and the diamond step does not finish after running for 7 days. I am using the uniref50 database and it is the only one in my data/uniref folder.

I previously did QC with trimmomatic so did not use knead data, and I concatenated my QC forward and reverse reads for input. I had the impression from reading the docs that knead data was not necessary, but after looking into knead data more I see that it can filter rRNA. So I’m wondering if filtering rRNA with knead data prior to running humann is suggested reduce run time?

  1. I would greatly appreciate some clarification as to if removing rRNA with knead data would reduce humann’s run time.
  2. If indeed filtering rRNA with knead data is recommended, could I filter the bowtie2_unaligned.fa file from humann and proceed with --resume? Or would I need to delete all the intermediate temp output files and start over?

Thanks!
Grace

2

Hi Grace, Thanks for reaching out! How many cores are you using for your HUMAnN run? Also how large is your input file? Unless you are running with a single core and you have a very large input file, that run time seems very long. Do you see any errors in any logs? If you expect contamination in your samples I would suggest running Kneaddata in addition to the QC you ran. The only way Kneaddata would reduce the HUMAnN run time was if it filtered a significant number of your reads (so HUMAnN had significantly less reads to align).

Thank you,
Lauren