Microbial Genomics · 2021 · 1.3K citations · 53 references
Life SciencesBioinformaticsMicrobiologyGenomicsMetagenomicsMicrobial GenomicsComparative Microbial GenomicsMetagenome AssemblyMetagenomic AnalysisMetagenomic AnnotationMicrobial ProteomicsAlignment-free Sequence ComparisonCommand-line AutomationFunctional Categories AcquisitionGenome Annotation PipelinesMetagenome-assembled GenomesMicrobial Genome AnnotationProkaryotic Sequence AnnotationReference Benchmarks
Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.
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