R package phytools: Phylogenetic Tools for comparative biology (and other things): Package contains various functions for phylogenetic analysis. This functionality is concentrated in the phylogenetic analysis of comparative data from species. For example, the package includes functions for Bayesian and ML ancestral state estimation; visual simulation of trait evolution; fitting models of trait evolution with multiple Brownian rates and correlations; visualizing discrete and continuous character evolution using colors or projections into trait space; identifying the location of a change in the rate of character evolution on the tree; fast Brownian motion simulation and simulation under several other models of continuous trait evolution; fitting a model of correlated binary trait evolution; locating the position of a fossil or an recently extinct lineage on a tree using continuous character data with ML; plotting lineage accumulation through time, including across multiple trees (such as a Bayesian posterior sample); conducting an analysis called stochastic character mapping, in which character histories for a discrete trait are sampled from their posterior probability distribution under a model; conducting a multiple (i.e., partial) Mantel test; fitting a phylogenetic regression model with error in predictor and response variables; conducting a phylogenetic principal components analysis, a phylogenetic regression, a reduced major axis regression, a phylogenetic canonical correlation analysis, and a phylogenetic ANOVA; projecting a tree onto a geographic map; simulating discrete character histories on the tree; and fitting a model in which a discrete character evolves under the threshold model. In addition to this phylogenetic comparative method functionality, the package also contains functions for a wide range of other purposes in phylogenetic biology. For instance, functionality in this package includes (but is not restricted to): adding taxa to a tree (including randomly, everywhere, or automatically to genera); generating all bi- and multi-furcating trees for a set of taxa; reducing a phylogeny to its backbone tree; dropping tips or adding tips to special types of phylogenetic trees; exporting a tree as an XML file; converting a tree with a mapped character to a tree with singleton nodes and one character state per edge; estimating a phylogeny using the least squares method; simulating birth-death trees under a range of conditions; rerooting trees; a wide range of visualizations of trees; and a variety of other manipulations and analyses that phylogenetic biologists may find useful for their research.

References in zbMATH (referenced in 10 articles )

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  1. Shaun Wilkinson, Simon Davy: phylogram: an R package for phylogenetic analysis with nested lists (2018) not zbMATH
  2. Uyttendaele, Nathan: On the estimation of nested Archimedean copulas: a theoretical and an experimental comparison (2018)
  3. Venelin Mitov; Krzysztof Bartoszek; Georgios Asimomitis; Tanja Stadler: Fast likelihood evaluation for multivariate phylogenetic comparative methods: the PCMBase R package (2018) arXiv
  4. Keith, Jonathan M. (ed.): Bioinformatics. Volume I. Data, sequence analysis, and evolution (2017)
  5. Wicke, Kristina; Fischer, Mareike: Comparing the rankings obtained from two biodiversity indices: the fair proportion index and the Shapley value (2017)
  6. Ioanna Manolopoulou, Axel Hille: BPEC: An R Package for Bayesian Phylogeographic and Ecological Clustering (2016) arXiv
  7. Carl Boettiger, Scott Chamberlain, Rutger Vos, Hilmar Lapp: RNeXML: a package for reading and writing richly annotated phylogenetic, character, and trait data in R (2015) arXiv
  8. Cybis, Gabriela B.; Sinsheimer, Janet S.; Bedford, Trevor; Mather, Alison E.; Lemey, Philippe; Suchard, Marc A.: Assessing phenotypic correlation through the multivariate phylogenetic latent liability model (2015)
  9. Elliot, Michael G.: Identical inferences about correlated evolution arise from ancestral state reconstruction and independent contrasts (2015)
  10. Swenson, Nathan G.: Functional and phylogenetic ecology in R (2014)