Description

Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle

Input

name:type
description
pattern

meta:map

Groovy Map containing sample information e.g. [ id:‘test’, single_end

]

fasta:file

FASTA file of assembled contigs.

*.{fa,fa.gz,fasta,fasta.gz,fna,fna.gz}

Output

name:type
description
pattern

classifications

meta:map

Groovy Map containing sample information e.g. [ id:‘test’, single_end

]

${prefix}.{txt,txt.gz}:file

TSV file containing per-contig classification probabilities and overall classifications. Gzipped if flag —gz is set.

*.{txt,txt.gz}

log

meta:map

Groovy Map containing sample information e.g. [ id:‘test’, single_end

]

log_*.{txt,txt.gz}:file

Log file containing tiara model parameters. Gzipped if flag —gz is set.

log_*.{txt,txt.gz}

fasta

meta:map

Groovy Map containing sample information e.g. [ id:‘test’, single_end

]

*.{fasta,fasta.gz}:file

(optional) - fasta files for each domain category specified in command flag -tf, containing classified contigs

*.{fasta,fasta.gz}

versions

versions.yml:file

File containing software versions

versions.yml

Tools

tiara
MIT

Deep-learning-based approach for identification of eukaryotic sequences in the metagenomic data powered by PyTorch.