Dear Humann3 team,
I would like to run this pipeline ASaiM - Galaxy Community Hub called ASAIM MT but using metaphlan 4 and humann3. Unfortunately, at the end of the humann3 command, I only get unclassified results:
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UniRef50_A0A3B9P6A7 | 17928.3447331564 |
UniRef50_A0A3B9P6A7 | unclassified |
UniRef50_W4V7T4 | 17254.9255236297 |
UniRef50_W4V7T4 | unclassified |
UniRef50_A3DBR3 | 10575.1057587066 |
UniRef50_A3DBR3 | unclassified |
UniRef50_A3DEF5: Fimbrial assembly family protein | 371.1157718711 |
UniRef50_A3DEF5: Fimbrial assembly family protein | unclassified |
Instead of this type of results (obtained with Humann2 on the same data) with the species:
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UniRef50_P62593: Beta-lactamase TEM | 51842.43044 |
UniRef50_P62593: Beta-lactamase TEM | g__Clostridium.s__Clostridium_thermocellum |
UniRef50_R5FV61 | 46966.29231 |
UniRef50_R5FV61 | g__Clostridium.s__Clostridium_thermocellum |
I find it strange that the species appear in the temp data of humann3:
SRR6820516.37548293754829/1 1515__A3DEF5__AD2_01123|k__Bacteria.p__Firmicutes.c__Clostridia.o__Clostridiales.f__Hungateiclostridiaceae.g__Hungateiclostridium.s__Hungateiclostridium_thermocellum|UniRef90_A3DEF5|UniRef50_A3DEF5|552 96.68874172185431 151.0 0 150.0 404 553 0
Is this normal?
Maybe I have a problem with the specification of the mpa_vJan21 database?
For your reference, I ran the following commands:
metaphlan “$output_dir/cutadapt_interlacer/pairs.fq” --input_type fastq -o “$output_dir/metaphlan/results.dat” --no_map -t ‘rel_ab’ --tax_lev ‘a’ --min_cu_len ‘2000’ --min_alignment_len ‘0’ --stat_q ‘0.1’ -s “$output_dir/metaphlan/sam_output_file.dat” --biom “$output_dir/metaphlan/biom_output_file.dat” --index mpa_vJan21_CHOCOPhlAnSGB_202103
humann --input $output_dir/sortmerna_interlacer/pairs.fq --output $output_dir/humann --taxonomic-profile “$output_dir/metaphlan/results.dat” --metaphlan-options="–index mpa_vJan21_CHOCOPhlAnSGB_202103 -t rel_ab " --nucleotide-database db/chocophlan --translated-alignment ‘diamond’ --protein-database ‘db/uniref/uniref50’ --search-mode ‘uniref50’ --pathways ‘metacyc’ --annotation-gene-index 8 --evalue ‘1.0’ --memory-use minimum --prescreen-threshold ‘0.01’ --nucleotide-identity-threshold ‘50.0’ --translated-identity-threshold ‘50.0’ --translated-subject-coverage-threshold ‘50.0’ --translated-query-coverage-threshold ‘50.0’ --xipe ‘off’ --minpath ‘on’ --gap-fill ‘on’ --output-format ‘tsv’ --output-max-decimals ‘10’ --output-basename ‘humann’ --threads 4
And I use the sample data of the ASAIM MT training:
Metatranscriptomics analysis using microbiome RNA-seq data (short) available at Training Data for "Metatranscriptomics analysis using microbiome RNASeq data" | Zenodo
Thank you for your time and assistance.
Best regards,
Jérémy Tournayre