Your browser doesn't support javascript.
loading
ClockstaRX: Testing Molecular Clock Hypotheses With Genomic Data.
Duchêne, David A; Duchêne, Sebastián; Stiller, Josefin; Heller, Rasmus; Ho, Simon Y W.
Afiliação
  • Duchêne DA; Center for Evolutionary Hologenomics, University of Copenhagen, Copenhagen 1352, Denmark.
  • Duchêne S; Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen 1352, Denmark.
  • Stiller J; Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3010, Australia.
  • Heller R; Villum Centre for Biodiversity Genomics, University of Copenhagen, 2100 Copenhagen, Denmark.
  • Ho SYW; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark.
Genome Biol Evol ; 16(4)2024 04 02.
Article em En | MEDLINE | ID: mdl-38526019
ABSTRACT
Phylogenomic data provide valuable opportunities for studying evolutionary rates and timescales. These analyses require theoretical and statistical tools based on molecular clocks. We present ClockstaRX, a flexible platform for exploring and testing evolutionary rate signals in phylogenomic data. Here, information about evolutionary rates in branches across gene trees is placed in Euclidean space, allowing data transformation, visualization, and hypothesis testing. ClockstaRX implements formal tests for identifying groups of loci and branches that make a large contribution to patterns of rate variation. This information can then be used to test for drivers of genomic evolutionary rates or to inform models for molecular dating. Drawing on the results of a simulation study, we recommend forms of data exploration and filtering that might be useful prior to molecular-clock analyses.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Evolução Molecular / Modelos Genéticos Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Evolução Molecular / Modelos Genéticos Idioma: En Ano de publicação: 2024 Tipo de documento: Article