Skip to page navigation menu Skip entire header
Brown University
Skip 13 subheader links

Genome assembly by Bayesian Inference (GABI): sample report for PhiX174

Description

Abstract:
Genome Assembly by Bayesian Inference (GABI) is a prototype of a Bayesian framework for sequence assembly. Most genome assemblers construct point estimates, choosing only a single genome sequence from among many alternative hypotheses that are supported by the data. GABI uses a Markov chain Monte Carlo (MCMC) 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. GABI provides multiple ways for summarizing the results of an MCMC analysis. This sample report illustrates its application to Illumina test data for the bacteriophage PhiX174. It includes a FASTA file for the majority-rule consensus, annotated with the posterior probabilities of its components, and an interactive animation of the sampling for each MCMC chain, created with the D3jsdata visualization toolkit. GABI is freely available under a GPL license from https://bitbucket.org/mhowison/gabi.
Notes:
This work was supported by the National Science Foundation (http://www.nsf.gov) through the Alan T. Waterman Award to CW Dunn and award DEB-1026611 to EJ Edwards, and through additional support from Brown Division of Biology and Medicine (http://biomed.brown.edu) to EJ Edwards

Access Conditions

Use and Reproduction
This work is licensed under a GNU GPL3 License

Citation

Howison, Mark, Zapata, F., Edwards, Erika J., et al., "Genome assembly by Bayesian Inference (GABI): sample report for PhiX174 " (2014). Brown University Open Data Collection. Brown Digital Repository. Brown University Library. https://doi.org/http://dx.doi.org/10.7301/Z0H41PB7

Relations

Collection:

  • Brown University Open Data Collection

    This collection contains open and publicly-funded data sets created by Brown University faculty and student researchers. Increasingly, publishers, and funders are requiring that protocols, data sets, metadata, and code underlying published research be retained and preserved, their locations cited within …
    ...