HyPhy 2.5 - A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies

Sergei L. Kosakovsky Pond, Art F.Y. Poon, Ryan Velazquez, Steven Weaver, N. Lance Hepler, Ben Murrell, Stephen D. Shank, Brittany Rife Magalis, Dave Bouvier, Anton Nekrutenko, Sadie Wisotsky, Stephanie J. Spielman, Simon D.W. Frost, Spencer V. Muse

Research output: Contribution to journalArticlepeer-review

242 Scopus citations


HYpothesis testing using PHYlogenies (HyPhy) 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 backward compatible with previous HyPhy releases.

Original languageEnglish (US)
Pages (from-to)295-299
Number of pages5
JournalMolecular biology and evolution
Issue number1
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics


Dive into the research topics of 'HyPhy 2.5 - A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies'. Together they form a unique fingerprint.

Cite this