Unsupervised statistical clustering of environmental shotgun sequences

BackgroundThe development of effective environmental shotgun sequence binning methods remains an ongoing challenge in algorithmic analysis of metagenomic data. While previous methods have focused primarily on supervised learning involving extrinsic data, a first-principles statistical model combined with a self-training fitting method has not yet been developed.ResultsWe derive an unsupervised, maximum-likelihood formalism for clustering short …