Authors
Sergei L Kosakovsky Pond, Art FY 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 DW Frost, Spencer V Muse
Publication date
2020/1
Journal
Molecular biology and evolution
Volume
37
Issue
1
Pages
295-299
Publisher
Oxford University Press
Description
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.
Total citations
2020202120222023202435629511280
Scholar articles
SL Kosakovsky Pond, AFY Poon, R Velazquez… - Molecular biology and evolution, 2020