Bakta

Bakta is a tool for the rapid and standardized annotation of bacterial genomes, metagenome-assembled genomes (MAGs) and plasmids. It annotates tRNA, rRNA and other non-coding RNA genes, CRISPR arrays and protein-coding genes, and identifies known proteins with a fast, alignment-free sequence lookup. The results are written in standard formats such as GFF3, GenBank, EMBL and TSV.

Bakta

License

Free to use and open source under GNU GPLv3.

Available

Roihu-CPU: 1.11.4 (module py-bakta), via the bio-apps module.

Usage

Bakta is part of the bio-apps collection on Roihu. Load the bio-apps module tree and then the Bakta module:

module load bio-apps/v202603
module load py-bakta/1.11.4

Database

Bakta needs a reference database. CSC provides the full Bakta database (version 6.0), including the AMRFinderPlus database, in /dataset/project_2020345/bakta/db. The py-bakta module sets the BAKTA_DB environment variable to this directory, so you don't need to give the --db option. CSC keeps the shared database up to date, so you don't need to run bakta_db download or amrfinder_update yourself.

Annotating a genome

Annotate a genome assembly with:

bakta --output results --prefix sample1 --threads 8 assembly.fasta

Useful options include:

--genus, --species and --strain: organism information for the output files.
--locus-tag: locus tag prefix.
--complete: all sequences are complete replicons (chromosomes or plasmids).
--meta: metagenome mode for gene prediction, for example for MAGs.
--compliant: make the output compliant with GenBank, ENA and DDBJ.
--skip-plot: skip the circular genome plot.

Run bakta --help for the full list of options. The results are written to the --output directory: the annotations as sample1.tsv, sample1.gff3, sample1.gbff and sample1.embl, the sequences as sample1.fna, sample1.ffn and sample1.faa, and a summary in sample1.txt.

To annotate protein sequences instead of a genome, use bakta_proteins. It uses the same database; see bakta_proteins --help.

Example batch script

#!/bin/bash
#SBATCH --job-name=bakta
#SBATCH --account=<project>
#SBATCH --output=output_%j.txt
#SBATCH --error=errors_%j.txt
#SBATCH --partition=small
#SBATCH --time=02:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --mem-per-cpu=2G

module load bio-apps/v202603
module load py-bakta/1.11.4

bakta --output results --prefix sample1 --threads $SLURM_CPUS_PER_TASK assembly.fasta

Replace <project> with your CSC project (for example project_2001234).

See creating a batch job script for Roihu for more information about running batch jobs.

Support

CSC Service Desk