Large constant run time cost to metaphlan?

Microbial community profiling MetaPhlAn
1

I’m trying out humann3, the newest metaphlan, MetaPhlAn version 3.0.1 (25 Jun 2020), running with bowtie2-align version 2.1.0.

The command is

/home/wbazant/.local/bin/metaphlan /home/wbazant/humann-nextflow/work/7e/c273ef3d436cddae2cc3c259455373/reads.fastq -t rel_ab -o /home/wbazant/humann-nextflow/work/7e/c273ef3d436cddae2cc3c259455373/reads_humann_temp/reads_metaphlan_bugs_list.tsv --input_type fastq --bowtie2out /home/wbazant/humann-nextflow/work/7e/c273ef3d436cddae2cc3c259455373/reads_humann_temp/reads_metaphlan_bowtie2.txt --nproc 4

It spends time in bowtie2-align building an index,

bowtie2-align --wrapper basic-0 --very-sensitive -x /home/wbazant/.local/lib/python3.7/site-packages/metaphlan/metaphlan_databases/mpa_v30_CHOCOPhlAn_201901 -p 4 --passthrough -U - --quiet

When using a tiny file with 20 mito reads this is the cost of this part:

    CPU time :                                   1229.94 sec.
    Max Memory :                                 2290 MB
    Average Memory :                             1699.60 MB
    Run time :                                   741 sec.

Is this unavoidable? What are the typical index load times like, with the standard chocophlan, in an efficient setup?

I’m running this in a cluster environment, but without any care for the details (yet).

First potential problem is that I’m using an old bowtie, which didn’t pick up this change:

bowtie2.2

  • Improved way in which index files are loaded for alignment. Should fix efficiency problems on some filesystems.

and a second is that I’m storing an index in a low-end filesystem (just where my python modules are, the way metaphlan installed it by default).

2

Unfortunately, no, the index is needed to be load into memory to perform the mapping. On my machine the index is loaded in 6.61 s ± 216 ms but the measure you are referring to is the full mapping of the input to the index