PT  - JOURNAL ARTICLE
AU  - Dongwan D. Kang
AU  - Jeff Froula
AU  - Rob Egan
AU  - Zhong Wang
TI  - A robust statistical framework for reconstructing genomes from metagenomic data
AID  - 10.1101/011460
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 011460
4099  - http://biorxiv.org/content/early/2014/11/15/011460.short
4100  - http://biorxiv.org/content/early/2014/11/15/011460.full
AB  - We present software that reconstructs genomes from shotgun metagenomic sequences using a reference-independent approach. This method permits the identification of OTUs in large complex communities where many species are unknown. Binning reduces the complexity of a metagenomic dataset enabling many downstream analyses previously unavailable. In this study we developed MetaBAT, a robust statistical framework that integrates probabilistic distances of genome abundance with sequence composition for automatic binning. Applying MetaBAT to a human gut microbiome dataset identified 173 highly specific genomes bins including many representing previously unidentified species.