Automated Gene Structure Annotation Using EVidenceModeler
Author Information
Author(s): Brian J. Haas, Steven L. Salzberg, Wei Zhu, Mihaela Pertea, Jonathan E. Allen, Joshua Orvis, Owen White, C. Robin Buell, Jennifer R. Wortman
Primary Institution: J Craig Venter Institute, The Institute for Genomic Research
Hypothesis
Can EVidenceModeler (EVM) produce automated gene structure annotations that approach the quality of manual curation?
Conclusion
EVM is an effective automated gene structure annotation tool that leverages ab initio gene predictions and sequence homologies to generate weighted consensus gene predictions.
Supporting Evidence
- EVM produces automated gene structure annotation approaching the quality of manual curation.
- Combining multiple sources of evidence improves gene prediction accuracy.
- EVM was applied to both rice and human genome sequences.
Takeaway
This study shows that a computer program can help scientists find genes in DNA, making it faster and easier than doing it by hand.
Methodology
EVM combines evidence from multiple gene prediction programs and spliced alignments to produce consensus gene structures.
Limitations
The accuracy of EVM is dependent on the quality of the input evidence and may not perform as well in the absence of high-quality data.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website