RT Journal Article
SR Electronic
T1 A robust statistical framework for reconstructing genomes from metagenomic data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 011460
DO 10.1101/011460
A1 Dongwan D. Kang
A1 Jeff Froula
A1 Rob Egan
A1 Zhong Wang
YR 2014
UL http://biorxiv.org/content/early/2014/11/15/011460.abstract
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.