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Author Notes:

Phone +49-(0)3834-420-4642, Fax +49-(0)3834-420-4640, katharina.hoff@uni-greifswald.de, boorodoovsky@gatech.edu

Subjects:

Research Funding:

This work is supported in part by the US National Institutes of Health grant HG000783 to MB and by German Research Foundation grant 1009/12–1 to MS.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biochemical Research Methods
  • Biochemistry & Molecular Biology
  • Protein-coding genes
  • Gene prediction
  • AUGUSTUS
  • GeneMark-ES/ET
  • RNA-Seq reads
  • Protein mapping to genome
  • Genome annotation pipeline
  • BRAKER
  • ALIGNMENT
  • IDENTIFICATION
  • PREDICTION
  • SEQUENCES
  • FUNGAL

Whole-Genome Annotation with BRAKER

Tools:

Journal Title:

GENE PREDICTION: METHODS AND PROTOCOLS

Volume:

Volume 1962

Publisher:

, Pages 65-95

Type of Work:

Article | Post-print: After Peer Review

Abstract:

BRAKER is a pipeline for highly accurate and fully automated gene prediction in novel eukaryotic genomes. It combines two major tools: GeneMark-ES/ET and AUGUSTUS. GeneMark-ES/ET learns its parameters from a novel genomic sequence in a fully automated fashion; if available, it uses extrinsic evidence for model refinement. From the protein-coding genes predicted by GeneMark-ES/ET, we select a set for training AUGUSTUS, one of the most accurate gene finding tools that, in contrast to GeneMark-ES/ET, integrates extrinsic evidence already into the gene prediction step. The first published version, BRAKER1, integrated genomic footprints of unassembled RNA-Seq reads into the training as well as into the prediction steps. The pipeline has since been extended to the integration of data on mapped cross-species proteins, and to the usage of heterogeneous extrinsic evidence, both RNA-Seq and protein alignments. In this book chapter, we briefly summarize the pipeline methodology and describe how to apply BRAKER in environments characterized by various combinations of external evidence.

Copyright information:

© Springer Science+Business Media, LLC, part of Springer Nature 2019.

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