HyPhy 2.5 - a customizable platform for evolutionary hypothesis testing using phylogenies.

By Sergei L. Kosakovsky Pond, Art F. Y. Poon, Ryan Velazquez, Scott Weaver, N. Hepler, Ben Murrell, Stephen D. Shank, B. Magalis, Dave Bouvier, Anton Nekrutenko and 4 more. Molecular biology and evolution, 2019

605 citations recorded by the source corpus.

hyphy (HYpothesis testing using PHYlogenies) is a scriptable, open-source package for fitting a broad range of evolutionary models to multiple sequence alignments, and for conducting subsequent parameter estimation and hypothesis testing, primarily in the maximum likelihood statistical framework. It has become a popular choice for characterizing various aspects of the evolutionary process: natural selection, evolutionary rates, recombination, and coevolution. The 2.5 release (available from www.hyphy.org) includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backwards compatible with previous HyPhy releases.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ed7b9dd70cfb685e7536d1ae3ecdf9d9c10c567f

Citations in the corpus

• Changing the Optics: Comparing Traditional and Retrieval-Augmented GenAI E-Tutorials in Interdisciplinary Learning (2026, unknown): “…information through GenAI influences users’ orienteering behaviors, we conducted a between-subjects experimental study with 10 participants who are at least 18 years old, speak and read fluent English, studying computer science at Temple University, and have not previously used HyPhy [12, 10].”