4.7 Article

apex: phylogenetics with multiple genes

期刊

MOLECULAR ECOLOGY RESOURCES
卷 17, 期 1, 页码 19-26

出版社

WILEY
DOI: 10.1111/1755-0998.12567

关键词

genetics; package; phylogenies; R; software

资金

  1. Medical Research Council Centre for Outbreak Analysis
  2. National Institute for Health Research - Health Protection Research Unit (NIHR HPRU) in Modelling Methodology at Imperial College London
  3. Public Health England (PHE)
  4. National Science Foundation [DEB 1350474]
  5. United States Department of Agriculture (USDA) Agricultural Research Service (ARS) [5358-22000-039-00D]
  6. USDA Animal and Plant Health Inspection Service
  7. USDA-ARS Floriculture Nursery Initiative
  8. Oregon Department of Agriculture/Oregon Association of Nurseries (ODA-OAN)
  9. USDA Forest Service Forest Health Monitoring Program
  10. Medical Research Council [MR/K010174/1B] Funding Source: researchfish
  11. National Institute for Health Research [HPRU-2012-10080] Funding Source: researchfish

向作者/读者索取更多资源

Genetic sequences of multiple genes are becoming increasingly common for a wide range of organisms including viruses, bacteria and eukaryotes. While such data may sometimes be treated as a single locus, in practice, a number of biological and statistical phenomena can lead to phylogenetic incongruence. In such cases, different loci should, at least as a preliminary step, be examined and analysed separately. The R software has become a popular platform for phylogenetics, with several packages implementing distance-based, parsimony and likelihood-based phylogenetic reconstruction, and an even greater number of packages implementing phylogenetic comparative methods. Unfortunately, basic data structures and tools for analysing multiple genes have so far been lacking, thereby limiting potential for investigating phylogenetic incongruence. In this study, we introduce the new R package apex to fill this gap. apex implements new object classes, which extend existing standards for storing DNA and amino acid sequences, and provides a number of convenient tools for handling, visualizing and analysing these data. In this study, we introduce the main features of the package and illustrate its functionalities through the analysis of a simple data set.

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