PT  - JOURNAL ARTICLE
AU  - Ahmed A. Metwally
AU  - Yang Dai
AU  - Patricia W. Finn
AU  - David L. Perkins
TI  - WEVOTE: Weighted Voting Taxonomic Identification Method of Microbial Sequences
AID  - 10.1101/054205
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 054205
4099  - http://biorxiv.org/content/early/2016/08/11/054205.short
4100  - http://biorxiv.org/content/early/2016/08/11/054205.full
AB  - Metagenome shotgun sequencing presents opportunities to identify organisms that may prevent or promote disease. The analysis of sample diversity is achieved by taxonomic identification of metagenomic reads followed by generating an abundance profile. Numerous tools have been developed based on different design principles. Tools achieving high precision can lack sensitivity in some applications. Conversely, tools with high sensitivity can suffer from low precision and require long computation time. In this paper, we present WEVOTE (WEighted VOting Taxonomic idEntification), a method that classifies metagenome shotgun sequencing DNA reads based on an ensemble of existing methods using k-mer-based, marker-based, and naive-similarity based approaches. Our evaluation on fourteen benchmarking datasets shows that WEVOTE improves the classification precision by reducing false positive annotations while preserving a high level of sensitivity. WEVOTE is an efficient and automated tool that combines multiple individual taxonomic identification methods to produce more precise and sensitive microbial profiles. WEVOTE is developed primarily to identify reads generated by MetaGenome Shotgun sequencing. It is expandable and has the potential to incorporate additional tools to produce a more accurate taxonomic profile. WEVOTE was implemented using C++ and shell scripting and is available at www.bitbucket.org/ametwally/wevoteWEVOTEWEighted VOting Taxonomic idEntification methodMGSMetaGenome ShotgunLCALowest Common AncestorNCBINational Center for Biotechnology Information