Weaver Steven, Shank Stephen D, Spielman Stephanie J, Li Michael, Muse Spencer V, Kosakovsky Pond Sergei L
Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.
Department of Statistics, North Carolina State University, Raleigh, NC.
Mol Biol Evol. 2018 Mar 1;35(3):773-777. doi: 10.1093/molbev/msx335.
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.
推断进化力量如何塑造现存的遗传多样性是现代比较序列分析的基石。序列生成技术的进步以及相关方法在统计方面的日益成熟，使得研究人员现在能够从数据中提取越来越多的进化信号，尽管计算成本有所增加。在此，我们宣布发布Datamonkey 2.0，这是Datamonkey网络服务器的一个完全重新设计的版本，用于分析序列数据中的进化特征。为此，我们利用了开源库的最新发展，这些发展有助于开发交互式、稳健且可扩展的网络应用程序。Datamonkey 2.0提供了精心策划的一系列方法，用于审视编码序列比对中的自然选择印记，并将其打包成一个响应式（即可以在平板电脑和移动设备上查看）、完全交互式且支持API的网络应用程序。为了补充Datamonkey 2.0，我们还发布了HyPhy Vision，这是一个用于可视化分析结果的配套JavaScript应用程序。HyPhy Vision也可以与Datamonkey 2.0分开使用，以可视化本地执行的HyPhy分析。Datamonkey 2.0和HyPhy Vision共同展示了科学软件开发如何能够从通用开源框架中受益。Datamonkey 2.0可在http://www.datamonkey.org免费公开获取，其底层代码库可从https://github.com/veg/datamonkey-js获取。
