Modeling Phylogenetic Signals using Eigenvector Maps
Computational tools to represent phylogenetic signals using adapted eigenvector maps.
Phylogenetic eignevector maps (PEM) is a method for using phylogeny to model features of organism, most notably quantitative traits. It consists in calculating sets of explanatory variables (eigenvectors) that are meant to represent different patters in trait values that are likely to have been inducted by evolution. These patterns are used to model the data (using a linear model for instance).
If one gets a ‘target’ species (i.e. a species for which the trait value is unknown), and providing that we know the phylogenetic relationships between that species and those of the model, the method allows to obtain the scores of that new species on the phylogenetic eigenfunctions underlying a PEM. These scores are used to make empirical predictions of trait values for the target species on the basis of those observed for the species of the model.
Functions PEM.build, PEM.updater,
PEM.fitSimple, and PEM.forcedSimple allows
one to build, update (i.e. recalculate with alternate weighting
parameters) as well as to estimate or force arbitrary values for the
weighting function parameters.
Functions getGraphLocations and
Locations2PEMscores allows one to make predictions using
method predict.PEM and a linear model. To obtain these
linear model, user can use function lm or auxiliary
functions lmforwardsequentialsidak or
lmforwardsequentialAICc, which perform forward-stepwise
variable addition on the basis of either familiwise type I error rate
or the Akaike Information Criterion (AIC), respectively.
The package provides low-level utility function for performing
operation on graphs (see graph-functions), calculate influence
matrix (PEMInfluence), and simulate trait values (see
trait-simulator).
A phylogenetic modeling tutorial using MPSEM is available as a
vignette (see example below).
The DESCRIPTION file:
| Package: | MPSEM |
| Version: | 0.3-6 |
| Date: | 2019-06-03 |
| Type: | Package |
| Title: | Modeling Phylogenetic Signals using Eigenvector Maps |
| Author: | Guillaume Guenard, with contribution from Pierre Legendre |
| Maintainer: | Guillaume Guenard <guillaume.guenard@gmail.com> |
| Description: | Computational tools to represent phylogenetic signals using adapted eigenvector maps. |
| Depends: | R (>= 3.0.0), ape, MASS |
| Suggests: | knitr, caper, xtable |
| VignetteBuilder: | knitr |
| License: | GPL (>= 2) |
| LazyLoad: | yes |
| NeedsCompilation: | yes |
Index of help topics:
MPSEM-package Modeling Phylogenetic Signals using Eigenvector
Maps
PEM-class Class and methods for Phylogenetic Eigenvector
Maps (PEM)
PEMInfluence Phylogenetic Eigenvector Map
TraitOUsimTree Simulates the evolution of a quantitative
trait.
graph-class Graph class and methods
graph-functions Graph creation and manipulation functions
lmforwardsequentialsidak
Linear modelling utility functionsGuillaume Guenard, with contribution from Pierre Legendre
Maintainer: Guillaume Guenard <guillaume.guenard@gmail.com>
Guénard, G., Legendre, P., and Peres-Neto, P. 2013. Phylogenetic eigenvector maps (PEM): a framework to model and predict species traits. Meth. Ecol. Evol. In press.
Makarenkov, V., Legendre, L. & Desdevise, Y. 2004. Modelling phylogenetic relationships using reticulated networks. Zool. Scr. 33: 89-96
Blanchet, F. G., Legendre, P. & Borcard, D. 2008. Modelling directional spatial processes in ecological data. Ecol. Model. 215: 325-336
### To view MPSEM tutorial
vignette("MPSEM", package="MPSEM")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.