Thomas Guillerme

Thomas Guillerme

3 packages on CRAN

dispRity

cran
99.99th

Percentile

A modular package for measuring disparity from multidimensional matrices. Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics (Guillerme (2018) <doi:10.1111/2041-210X.13022>). The package also provides functions for looking at disparity in a serial way (e.g. disparity through time - Guillerme and Cooper (2018) <doi:10.1111/pala.12364>) or per groups as well as visualising the results. Finally, this package provides several basic statistical tests for disparity analysis.

ape

cran
99.99th

Percentile

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 DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, 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, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. 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.

Claddis

cran
99.99th

Percentile

Measures morphological diversity from discrete character data and estimates evolutionary tempo on phylogenetic trees. Imports morphological data from #NEXUS (Maddison et al. (1997) <doi:10.1093/sysbio/46.4.590>) format with ReadMorphNexus(), and writes to both #NEXUS and TNT format (Goloboff et al. (2008) <doi:10.1111/j.1096-0031.2008.00217.x>). Main functions are DiscreteCharacterRate(), which implements likelihood ratio tests for discrete character rates introduced across Lloyd et al. (2012) <doi:10.1111/j.1558-5646.2011.01460.x>, Brusatte et al. (2014) <doi:10.1016/j.cub.2014.08.034>, Close et al. (2015) <doi:10.1016/j.cub.2015.06.047>, and Lloyd (2016) <doi:10.1111/bij.12746>, and MorphDistMatrix(), which implements multiple discrete character distance metrics from Gower (1971) <doi:10.2307/2528823>, Wills (1998) <doi:10.1006/bijl.1998.0255>, Lloyd (2016) <doi:10.1111/bij.12746>, and Hopkins and St John (2018) <doi:10.1098/rspb.2018.1784>. Multiple functions implement various morphospace plots: ChronoPhyloMorphospacePlot() implements Sakamoto and Ruta (2012) <doi:10.1371/journal.pone.0039752>, MorphospacePlot() implements Wills et al. (1994) <doi:10.1017/S009483730001263X>, PlotCharacterChanges() implements Wang and Lloyd (2016) <doi:10.1098/rspb.2016.0214>, and StackPlot() implements Foote (1993) <doi:10.1017/S0094837300015864>. Other functions include SafeTaxonomicReduction(), which implements Wilkinson (1995) <doi:10.1093/sysbio/44.4.501>, and DolloSCM() implements the Dollo stochastic character mapping of Tarver et al. (2018) <doi:10.1093/gbe/evy096>.