I run HUMAnN3.5 with MetaPhlAn4 in linux but get a error, here is error message in screen:
ERROR: The MetaPhlAn taxonomic profile provided was not generated with the expected database version. Please update your version of MetaPhlAn to at least v3.0.
These two software were installed by conda, an HUMAnN version is v3.5, MetaPhlAn version is 4.0.1 (24 Aug 2022), the database were download and config using humann_database and metaphlan --install. my command line was pasted below:
humann -i merge.fq -o sample --threads 30 --search-mode uniref90 --memory-use maximum --metaphlan-options “-t rel_ab_w_read_stats” --pathways unipathway
please tell me what’s wrong, I can’t fix it by myself.
PS. I have run humann_test and all thing is ok. I also have run MetaPhlAn4 separately, and it correctly worked, and same data was successfully tested using HUMAnN3.1 with MetaPhlAn3
Hello Nemo, Thank you for the detailed post and for testing each tools install. Would you try running again without the MetaPhlAn option “-t rel_ab_w_read_stats”? I think that changes the format of the output file which might cause HUMAnN to have an issue trying to read the relative abundances (as they might be placed in a different column then expected).
you are right, i have run humann3.5 with default parameter using same data and it working, so this error is conducted by option ‘-t rel_ab_w_read_stats’.
Nevertheless, I still hope get reads count to do some difference analysis like deseq2 and ancom, could there any solution for this？i also could run humann3.5 and metaphlan4 separately, but it seemly complicated.
Hi @axolotl233 - I removed your comment about this on the HUMAnN 3.6 post but can respond here. This is not a bug - HUMAnN requires MetaPhlAn’s default taxonomic profile output to function, so if you ask for a different style of output HUMAnN won’t be able to use it. If you run HUMAnN (with MetaPhlAn) the default way, you can use the MetaPhlAn bowtie2 output under HUMAnN’s temp folder to perform other MetaPhlAn analyses, including computing read stats. Since MetaPhlAn will be starting from pre-mapped input this will be very fast!
Hi, sorry for bother you again, i will do it as you suggested, thank you~