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

被引：378

作者：

Pond, Sergei L. Kosakovsky ^{[1
]}

Poon, Art F. Y. ^{[2
]}

Velazquez, Ryan ^{[1
]}

Weaver, Steven ^{[1
]}

Hepler, N. Lance ^{[3
]}

Murrell, Ben ^{[4
]}

Shank, Stephen D. ^{[1
]}

Magalis, Brittany Rife ^{[1
]}

Bouvier, Dave ^{[5
]}

Nekrutenko, Anton ^{[5
]}

Wisotsky, Sadie ^{[1
,6
]}

Spielman, Stephanie J. ^{[1
,7
]}

Frost, Simon D. W. ^{[8
,9
]}

Muse, Spencer, V ^{[6
]}

机构：

[1] Temple Univ, Inst Genom & Evolutionary Med, Philadelphia, PA 19122 USA

[2] Western Univ, Pathol & Lab Med, London, ON, Canada

[3] 10X Genom, Pleasanton, CA USA

[4] Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden

[5] Penn State Univ, Biochem & Mol Biol, State Coll, PA USA

[6] North Carolina State Univ, Dept Stat & Bioinformat Res Ctr, Raleigh, NC USA

[7] Rowan Univ, Glassboro, NJ USA

[8] Univ Cambridge, Dept Vet Med, Cambridge, England

[9] Alan Turing Inst, London, England

来源：

MOLECULAR BIOLOGY AND EVOLUTION | 2020年 / 37卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

evolutionary analysis; natural selection; hypothesis testing; statistical inference; software engineering; MODEL; SOFTWARE; SITES;

D O I：

10.1093/molbev/msz197

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页码：295 / 299

页数：5

共 27 条

[1]

[Anonymous], 2019, PLOS COMPUT BIOL

[2]

[Anonymous], SYST BIOL

[3]

Blankenberg Daniel, 2010, Curr Protoc Mol Biol, VChapter 19, DOI 10.1002/0471142727.mb1910s89

[4] Latent Dirichlet allocation [J].

Blei, DM ;

Ng, AY ;

Jordan, MI .

JOURNAL OF MACHINE LEARNING RESEARCH, 2003, 3 (4-5) :993-1022

[5] The State of Software for Evolutionary Biology [J].

Darriba, Diego ;

Flouri, Tomas ;

Stamatakis, Alexandros .

MOLECULAR BIOLOGY AND EVOLUTION, 2018, 35 (05) :1037-1046

[6] A hidden Markov Model approach to variation among sites in rate of evolution [J].

Felsenstein, J ;

Churchill, GA .

MOLECULAR BIOLOGY AND EVOLUTION, 1996, 13 (01) :93-104

[7] Bioconda: sustainable and comprehensive software distribution for the life sciences [J].

Gruening, Bjoern ;

Dale, Ryan ;

Sjoedin, Andreas ;

Chapman, Brad A. ;

Rowe, Jillian ;

Tomkins-Tinch, Christopher H. ;

Valieris, Renan ;

Koester, Johannes ;

Team, Bioconda .

NATURE METHODS, 2018, 15 (07) :475-476

[8] RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language [J].

Hohna, Sebastian ;

Landis, Michael J. ;

Heath, Tracy A. ;

Boussau, Bastien ;

Lartillot, Nicolas ;

Moore, Brian R. ;

Huelsenbeck, John P. ;

Ronquist, Fredrik .

SYSTEMATIC BIOLOGY, 2016, 65 (04) :726-736

[9]

Izquierdo-Carrasco Fernando, 2013, 2013 IEEE International Symposium on Parallel and Distributed Processing, Workshops and PhD Forum (IPDPSW), P530, DOI 10.1109/IPDPSW.2013.103

[10] Software Engineering for Computational Science: Past, Present, Future [J].

Johanson, Arne N. ;

Hasselbring, Wilhelm .

COMPUTING IN SCIENCE & ENGINEERING, 2018, 20 (02) :90-109

← 1 2 3 →