Publication | Open Access
Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes
995
Citations
24
References
2017
Year
Other Evolutionary ProcessesComparative GenomicsGeneticsEvolutionary ForcesNatural SelectionGenomicsBiological EvolutionEvolution StrategyPhylogeneticsData ScienceData MiningMolecular EcologyComputational GenomicsModern Web ApplicationGenome AnalysisData IntegrationEvolution-based MethodSequence AnalysisKnowledge DiscoveryDatamonkey 2.0Genetic VariationPopulation GeneticsFunctional GenomicsBioinformaticsBiologyEvolutionary Data MiningNatural SciencesEvolutionary BiologyEvolutionary TheoryReference GenomeMedicineData Modeling
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.
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