Bakta 1.8.0: rapid & standardized annotation of bacterial genomes, MAGs & plasmids
Bakta is a tool for the rapid & standardized annotation of bacterial genomes
and plasmids from both isolates and MAGs. It provides dbxref-rich and
sORF-including annotations in machine-readable
JSON & bioinformatics
standard file formats for automatic downstream analysis.
Comprehensive & taxonomy-independent database Bakta provides a large and taxonomy-independent database using UniProt’s entire UniRef protein sequence cluster universe. Thus, it achieves favourable annotations in terms of sensitivity and specificity along the broad continuum ranging from well-studied species to unknown genomes from MAGs.
Protein sequence identification Bakta exactly identifies known identical protein sequences (IPS) from RefSeq and UniProt allowing the fine-grained annotation of gene alleles (
AMR) or closely related but distinct protein families. This is achieved via an alignment-free sequence identification (AFSI) approach using full-length
MD5protein sequence hash digests.
Fast This AFSI approach substantially accellerates the annotation process by avoiding computationally expensive homology searches for identified genes. Thus, Bakta can annotate a typical bacterial genome in 10 ±5 min on a laptop, plasmids in a couple of seconds/minutes.
Database cross-references Fostering the FAIR principles, Bakta exploits its AFSI approach to annotate CDS with database cross-references (dbxref) to RefSeq (
WP_*), UniRef100 (
UniRef100_*) and UniParc (
UPI*). By doing so, IPS allow the surveillance of distinct gene alleles and streamlining comparative analysis as well as posterior (external) annotations of
hypotheticalprotein sequences which can be mapped back to existing CDS via these exact & stable identifiers (E. coli gene ymiA …more). Currently, Bakta identifies ~214.8 mio, ~199 mio and ~161 mio distinct protein sequences from UniParc, UniRef100 and RefSeq, respectively. Hence, for certain genomes, up to 99 % of all CDS can be identified this way, skipping computationally expensive sequence alignments.
FAIR annotations To provide standardized annotations adhearing to FAIR principles, Bakta utilizes a versioned custom annotation database comprising UniProt’s UniRef100 & UniRef90 protein clusters (FAIR -> DOI/DOI) enriched with dbxrefs (
EC) and annotated by specialized niche databases. For each db version we provide a comprehensive log file of all imported sequences and annotations.
Small proteins / short open reading frames Bakta detects and annotates small proteins/short open reading frames (sORF) which are not predicted by tools like
Expert annotation systems To provide high quality annotations for certain proteins of higher interest, e.g. AMR & VF genes, Bakta includes & merges different expert annotation systems. Currently, Bakta uses NCBI’s AMRFinderPlus for AMR gene annotations as well as an generalized protein sequence expert system with distinct coverage, identity and priority values for each sequence, currenlty comprising the VFDB as well as NCBI’s BlastRules.
Comprehensive workflow Bakta annotates ncRNA cis-regulatory regions, oriC/oriV/oriT and assembly gaps as well as standard feature types: tRNA, tmRNA, rRNA, ncRNA genes, CRISPR, CDS and pseudogenes.
GFF3 & INSDC conform annotations Bakta writes GFF3 and INSDC-compliant (Genbank & EMBL) annotation files ready for submission (checked via GenomeTools GFF3Validator, table2asn_GFF and ENA Webin-CLI for GFF3 and EMBL file formats, respectively for representative genomes of all ESKAPE species).
Bacteria & plasmids only Bakta was designed to annotate bacteria (isolates & MAGs) and plasmids, only. This decision by design has been made in order to tweak the annotation process regarding tools, preferences & databases and to streamline further development & maintenance of the software.
Reasoning By annotating bacterial genomes in a standardized, taxonomy-independent, high-throughput and local manner, Bakta aims at a well-balanced tradeoff between fully featured but computationally demanding pipelines like PGAP and rapid highly customizable offline tools like Prokka. Indeed, Bakta is heavily inspired by Prokka (kudos to Torsten Seemann) and many command line options are compatible for the sake of interoperability and user convenience. Hence, if Bakta does not fit your needs, please consider trying Prokka.
You can visualize bakta json files with this web viewer inside your browser.
Download the completed json annotation and upload it here to view your genome.
Activating the conda environment
Check out a node with
qrsh and then:
Using conda activate bakta
If your conda is set up as
you can run
conda activate bakta instead of the
source line above as well.
To use over SGE, add the
source line above to your shell script prior to the
Running over SGE
To use over SGE, include the source line above in a shell script prior to your commands, e.g.
And then run
hqsub 'bash ./run_bakta.sh' -r sge.bakta ....
Using hqsub –conda
You can also run:
hqsub 'conda activate bakta; bakta ...' -r sge.bakta --conda ...
Without having to write a separate shell script.
Location, version, DB info
The database is on version 5.0.
deepsig is included in this install:
If you run into problems with
deepsig, please let us know.