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

Steven Weaver¹, Stephen D Shank¹, Stephanie J Spielman¹

¹Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.

Molecular Biology and Evolution

|January 5, 2018

Summary

This summary is machine-generated.

Datamonkey 2.0 is a new web server for analyzing evolutionary signatures in genetic data. It offers interactive tools to detect natural selection in coding sequences, enhancing comparative sequence analysis.

Keywords:

evolutionary inference natural selection recombination statistical methods web application

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Area of Science:

Evolutionary biology
Bioinformatics
Computational biology

Background:

Understanding evolutionary forces shaping genetic diversity is crucial for modern comparative sequence analysis.
Advances in sequencing and statistical methods allow deeper evolutionary insights but increase computational demands.

Purpose of the Study:

To release Datamonkey 2.0, a re-engineered web server for analyzing evolutionary signatures in sequence data.
To provide researchers with an interactive, robust, and scalable platform for detecting natural selection.

Main Methods:

Leveraged open-source libraries for web application development.
Developed Datamonkey 2.0 as a responsive, interactive, and API-enabled web application.
Released HyPhy Vision, a JavaScript application for visualizing analysis results.

Main Results:

Datamonkey 2.0 offers a curated collection of methods for interrogating coding-sequence alignments.
The platform is accessible on various devices and enables API-enabled analyses.
HyPhy Vision facilitates visualization of both Datamonkey and local HyPhy analyses.

Conclusions:

Datamonkey 2.0 and HyPhy Vision demonstrate the benefits of open-source frameworks in scientific software development.
The new tools enhance the analysis of evolutionary signatures in genetic data.
These resources are freely available to the scientific community.