- and manipulating phylogenetic trees, analyses of comparative data
- in a phylogenetic framework, analyses of diversification and
- macroevolution, computing distances from allelic and nucleotide
- data, reading nucleotide sequences, and several tools such as
- Mantel's test, computation of minimum spanning tree, generalized
- skyline plots, estimation of absolute evolutionary rates and
- clock-like trees using mean path lengths, non-parametric rate
- smoothing 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).
+ 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.