CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies
Continuously varying traits such as body size or gene expression level evolve during the history of species or gene lineages. To test hypotheses about the evolution of such traits, the maximum likelihood (ML) method is often used. Here we introduce CoMET (Continuous-character Model Evaluation and Te...
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Series: | Evolutionary Bioinformatics |
Online Access: | https://doi.org/10.1177/117693430600200022 |
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doaj-a9ee7b65bd524402843a8bdc1bdc1b372020-11-25T03:24:45ZengSAGE PublishingEvolutionary Bioinformatics1176-93432006-01-01210.1177/117693430600200022CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on PhylogeniesChunghau Lee0Sigal Blay1Arne Ø. Mooers2Ambuj Singh3Todd H. Oakley4Department of Computer Science; University of California, Santa Barbara, CA 93106 USA.Department of Biological Sciences and IRMACS, 8888 University Drive, Simon Fraser University, Burnaby, BC V5A 1S6 Canada.Department of Biological Sciences and IRMACS, 8888 University Drive, Simon Fraser University, Burnaby, BC V5A 1S6 Canada.Department of Computer Science; University of California, Santa Barbara, CA 93106 USA.Department of Ecology Evolution and Marine Biology, University of California, Santa Barbara, CA 93106 USA.Continuously varying traits such as body size or gene expression level evolve during the history of species or gene lineages. To test hypotheses about the evolution of such traits, the maximum likelihood (ML) method is often used. Here we introduce CoMET (Continuous-character Model Evaluation and Testing), which is module for Mesquite that automates likelihood computations for nine different models offrait evolution. Due to its few restrictions on input data, CoMET is applicable to testing a wide range of character evolution hypotheses. The CoMET homepage, which links to freely available software and more detailed usage instructions, is located at http://www.lifesci.ucsb.edu/eemb/labs/oakley/software/comet.htm .https://doi.org/10.1177/117693430600200022 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chunghau Lee Sigal Blay Arne Ø. Mooers Ambuj Singh Todd H. Oakley |
spellingShingle |
Chunghau Lee Sigal Blay Arne Ø. Mooers Ambuj Singh Todd H. Oakley CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies Evolutionary Bioinformatics |
author_facet |
Chunghau Lee Sigal Blay Arne Ø. Mooers Ambuj Singh Todd H. Oakley |
author_sort |
Chunghau Lee |
title |
CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies |
title_short |
CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies |
title_full |
CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies |
title_fullStr |
CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies |
title_full_unstemmed |
CoMET: A Mesquite Package for Comparing Models of Continuous Character Evolution on Phylogenies |
title_sort |
comet: a mesquite package for comparing models of continuous character evolution on phylogenies |
publisher |
SAGE Publishing |
series |
Evolutionary Bioinformatics |
issn |
1176-9343 |
publishDate |
2006-01-01 |
description |
Continuously varying traits such as body size or gene expression level evolve during the history of species or gene lineages. To test hypotheses about the evolution of such traits, the maximum likelihood (ML) method is often used. Here we introduce CoMET (Continuous-character Model Evaluation and Testing), which is module for Mesquite that automates likelihood computations for nine different models offrait evolution. Due to its few restrictions on input data, CoMET is applicable to testing a wide range of character evolution hypotheses. The CoMET homepage, which links to freely available software and more detailed usage instructions, is located at http://www.lifesci.ucsb.edu/eemb/labs/oakley/software/comet.htm . |
url |
https://doi.org/10.1177/117693430600200022 |
work_keys_str_mv |
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