BRAKER1

BRAKER1 performs unsupervised eukaryotic gene prediction and genome annotation by integrating RNA-Seq data with GeneMark-ET and AUGUSTUS.

Key Features:

• Unsupervised training: Leverages RNA-Seq data for unsupervised training, eliminating the need for pre-trained parameters or expert-prepared training sets.
• Iterative GeneMark-ET training: Uses GeneMark-ET to perform iterative training on RNA-Seq data to generate initial gene structures.
• AUGUSTUS refinement: Employs AUGUSTUS to refine GeneMark-ET predictions by using the predicted gene structures for additional training and integrating RNA-Seq read information.
• Input requirements: Requires a genome assembly file and a BAM-formatted file containing spliced alignments of RNA-Seq reads to the genome.
• Performance comparison: Has been reported to achieve higher accuracy than MAKER2 when training and prediction are performed using only RNA-Seq data.

Scientific Applications:

• Eukaryotic genome annotation: Generating gene models for annotation of diverse eukaryotic genomes using RNA-Seq evidence.
• Comparative genomics: Providing gene predictions for comparative analyses across species.
• Evolutionary biology and large-scale projects: Supplying automated RNA-Seq-based gene predictions for evolutionary studies and large-scale genome projects.

Methodology:

GeneMark-ET performs iterative training on RNA-Seq data to produce initial gene structures, and AUGUSTUS refines those predictions by incorporating the predicted gene structures and RNA-Seq read information.