A robust statistical framework for reconstructing genomes from metagenomic data

A robust statistical framework for reconstructing genomes from metagenomic data

Dongwan Don Kang, Jeff Froula, Rob Egan, Zhong Wang
doi: http://dx.doi.org/10.1101/011460

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.

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