Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes

被引:672
作者
Weaver, Steven [1 ]
Shank, Stephen D. [1 ]
Spielman, Stephanie J. [1 ]
Li, Michael [1 ]
Muse, Spencer V. [2 ]
Pond, Sergei L. Kosakovsky [1 ]
机构
[1] Temple Univ, Inst Genom & Evolutionary Med, Philadelphia, PA 19122 USA
[2] North Carolina State Univ, Dept Stat, Raleigh, NC USA
关键词
natural selection; statistical methods; web application; recombination; evolutionary inference; POSITIVE SELECTION; SITES; PRESSURE; VIRUS;
D O I
10.1093/molbev/msx335
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:773 / 777
页数:5
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