| Literature DB >> 29301006 |
Steven Weaver1, Stephen D Shank1, Stephanie J Spielman1, Michael Li1, Spencer V Muse2, Sergei L Kosakovsky Pond1.
Abstract
Inference of how evolutionary forces have shaped extant genetic diversity is a cornerstone of modern comparative sequence analysis. Advances in sequence generation and increased statistical sophistication of relevant methods now allow researchers to extract ever more evolutionary signal from the data, albeit at an increased computational cost. Here, we announce the release of Datamonkey 2.0, a completely re-engineered version of the Datamonkey web-server for analyzing evolutionary signatures in sequence data. For this endeavor, we leveraged recent developments in open-source libraries that facilitate interactive, robust, and scalable web application development. Datamonkey 2.0 provides a carefully curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application. To complement Datamonkey 2.0, we additionally release HyPhy Vision, an accompanying JavaScript application for visualizing analysis results. HyPhy Vision can also be used separately from Datamonkey 2.0 to visualize locally executed HyPhy analyses. Together, Datamonkey 2.0 and HyPhy Vision showcase how scientific software development can benefit from general-purpose open-source frameworks. Datamonkey 2.0 is freely and publicly available at http://www.datamonkey.org, and the underlying codebase is available from https://github.com/veg/datamonkey-js.Keywords: evolutionary inference; natural selection; recombination; statistical methods; web application
Year: 2018 PMID: 29301006 PMCID: PMC5850112 DOI: 10.1093/molbev/msx335
Source DB: PubMed Journal: Mol Biol Evol ISSN: 0737-4038 Impact factor: 16.240