title: Bayesian genome assembly and assessment by markov chain monte carlo sampling.
abstract: Most genome assemblers construct point estimates, choosing only a single genome sequence from among many alternative hypotheses that are supported by the data. We present a Markov chain Monte Carlo approach to sequence assembly that instead generates distributions of assembly hypotheses with posterior probabilities, providing an explicit statistical framework for evaluating alternative hypotheses and assessing assembly uncertainty. We implement this approach in a prototype assembler, called Genome Assembly by Bayesian Inference (GABI), and illustrate its application to the bacteriophage [Formula: see text]X174. Our sampling strategy achieves both good mixing and convergence on Illumina test data for [Formula: see text]X174, demonstrating the feasibility of our approach. We summarize the posterior distribution of assembly hypotheses generated by GABI as a majority-rule consensus assembly. Then we compare the posterior distribution to external assemblies of the same test data, and annotate those assemblies by assigning posterior probabilities to features that are in common with GABI's assembly graph. GABI is freely available under a GPL license from https://bitbucket.org/mhowison/gabi.
authors: Center for Computation and Visualization, Brown University, Providence, Rhode Island, United States of America.
authors: Mark
authors: M
authors: Howison
authors: Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.
authors: Felipe
authors: F
authors: Zapata
authors: Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.
authors: Erika J
authors: EJ
authors: Edwards
authors: Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.
authors: Casey W
authors: CW
authors: Dunn
mesh_terms: D010584:Bacteriophage phi X 174 / Q000235:genetics*; D020451:Contig Mapping / Q000379:methods*; D016679:Genome, Viral; D011336:Probability; D012984:Software