z-logo
open-access-imgOpen Access
Gene-Wide Identification of Episodic Selection
Author(s) -
Ben Murrell,
Steven Weaver,
Martin D. Smith,
Joel O. Wertheim,
Sasha Murrell,
Anthony Aylward,
Kemal Eren,
Tristan Pollner,
Darren P. Martin,
Davey M. Smith,
Konrad Scheffler,
Sergei L. Kosakovsky Pond
Publication year - 2015
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/msv035
Subject(s) - biology , selection (genetic algorithm) , identification (biology) , a priori and a posteriori , metric (unit) , positive selection , negative selection , evolutionary biology , substitution (logic) , gene , computational biology , artificial intelligence , genetics , computer science , ecology , genome , philosophy , operations management , epistemology , economics , programming language
We present BUSTED, a new approach to identifying gene-wide evidence of episodic positive selection, where the non-synonymous substitution rate is transiently greater than the synonymous rate. BUSTED can be used either on an entire phylogeny (without requiring an a priori hypothesis regarding which branches are under positive selection) or on a pre-specified subset of foreground lineages (if a suitable a priori hypothesis is available). Selection is modeled as varying stochastically over branches and sites, and we propose a computationally inexpensive evidence metric for identifying sites subject to episodic positive selection on any foreground branches. We compare BUSTED with existing models on simulated and empirical data. An implementation is available on www.datamonkey.org/busted, with a widget allowing the interactive specification of foreground branches.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom