galba
galba predicts protein-coding gene structures in novel eukaryotic genomes using high-quality proteins from closely related species as references.
Key Features:
- Protein-to-genome alignment (miniprot): Uses miniprot, a rapid protein-to-genome aligner, to map reference proteins to target genomes.
- Ab initio gene prediction (AUGUSTUS): Uses AUGUSTUS to infer gene structures informed by protein alignments.
- Reference-driven annotation: Leverages high-quality proteins from closely related species as evidence when transcriptome data are unavailable.
- Automated pipeline: Integrates alignment and prediction steps into an automated workflow for genome-wide annotation.
- Scalability: Demonstrated performance on large vertebrate genomes.
- Cross-taxa applicability: Applied to multiple eukaryotic groups including insects, vertebrates, and land plants.
Scientific Applications:
- Genome annotation without transcriptomes: Predicts protein-coding genes in newly sequenced eukaryotic genomes when RNA-seq or transcriptome data are lacking.
- Vertebrate genome annotation: Annotates large vertebrate genomes using reference proteins and combined miniprot+AUGUSTUS prediction.
- Cross-kingdom eukaryotic annotation: Supports gene structure prediction across taxa such as insects and land plants using reference-driven evidence.
Methodology:
Align reference proteins to the target genome using miniprot and use the resulting alignments as evidence for gene structure prediction with AUGUSTUS within an automated pipeline.
Topics
Details
- License:
- Artistic-1.0
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Perl, Bash
- Added:
- 11/16/2022
- Last Updated:
- 11/24/2024
Operations
Publications
Brůna T, Li H, Guhlin J, Honsel D, Herbold S, Stanke M, Nenasheva N, Ebel M, Gabriel L, Hoff KJ. Galba: genome annotation with miniprot and AUGUSTUS. BMC Bioinformatics. 2023;24(1). doi:10.1186/s12859-023-05449-z. PMID:37653395. PMCID:PMC10472564.
PMID: 37653395
PMCID: PMC10472564
Funding: - National Institutes of Health: R01HG010040
- Deutsche Forschungsgemeinschaft: 277249973, 391397397
- Government of Mecklenburg-Vorpommern: Project Data Competency