ape

R package ape: Analyses of Phylogenetics and Evolution , ape provides functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from allelic and nucleotide data, reading and writing nucleotide sequences, and several tools such as Mantel’s test, minimum spanning tree, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 64 articles )

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  1. Carson, Jake; Ledda, Alice; Ferretti, Luca; Keeling, Matt; Didelot, Xavier: The bounded coalescent model: conditioning a genealogy on a minimum root date (2022)
  2. Paradis, Emmanuel: Reduced multidimensional scaling (2022)
  3. Freund, Fabian; Siri-Jégousse, Arno: The impact of genetic diversity statistics on model selection between coalescents (2021)
  4. Kersting, Sophie J.; Fischer, Mareike: Measuring tree balance using symmetry nodes -- a new balance index and its extremal properties (2021)
  5. Richards, Andrew; Kubatko, Laura: Bayesian-weighted triplet and quartet methods for species tree inference (2021)
  6. Cappello, Lorenzo; Palacios, Julia A.: Sequential importance sampling for multiresolution Kingman-Tajima coalescent counting (2020)
  7. Gero Szepannek: An Overview on the Landscape of R Packages for Credit Scoring (2020) arXiv
  8. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  9. Ignatieva, Anastasia; Hein, Jotun; Jenkins, Paul A.: A characterisation of the reconstructed birth-death process through time rescaling (2020)
  10. Jhwueng, Dwueng-Chwuan: Modeling rate of adaptive trait evolution using Cox-Ingersoll-Ross process: an approximate Bayesian computation approach (2020)
  11. Yourdkhani, Samaneh; Rhodes, John A.: Inferring metric trees from weighted quartets via an intertaxon distance (2020)
  12. Fukuyama, Julia: Adaptive gPCA: a method for structured dimensionality reduction with applications to microbiome data (2019)
  13. Ge, Li; Liu, Jiaguo; Zhang, Yusen; Dehmer, Matthias: Identifying anticancer peptides by using a generalized chaos game representation (2019)
  14. Monod, Anthea; Kališnik, Sara; Patiño-Galindo, Juan Ángel; Crawford, Lorin: Tropical sufficient statistics for persistent homology (2019)
  15. Royer-Carenzi, Manuela; Didier, Gilles: Testing for correlation between traits under directional evolution (2019)
  16. Tahir, Daniah; Glémin, Sylvain; Lascoux, Martin; Kaj, Ingemar: Modeling a trait-dependent diversification process coupled with molecular evolution on a random species tree (2019)
  17. Warnow, Tandy (ed.): Bioinformatics and phylogenetics. Seminal contributions of Bernard Moret (2019)
  18. Amiri, Saeid; Clarke, Bertrand S.; Clarke, Jennifer L.: Clustering categorical data via ensembling dissimilarity matrices (2018)
  19. Bartoszek, Krzysztof: Exact and approximate limit behaviour of the Yule tree’s cophenetic index (2018)
  20. Bivand, Roger S.; Wong, David W. S.: Comparing implementations of global and local indicators of spatial association (2018)

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