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7
:
Journal:
Bioinformatics
Article type: Applications note
Category: Phylogenetics
MaATiICCE: Mapping Transitions in Continuous Character Evolution
Andrew L. Hipp
Marcial Escudero
ABSTRACT
Summary: MaATiICCE is a new software package written in the R language
that implements an information-theoretic approach to estimating the
probability of continuous character transitions on phylogenetic trees. It
relies on and provides helper functions for the automates batch-analysis
of alternative models of character change utilizing the OUCH (R) R
package; allows users to account for estimates the relative support for
character changes having occurred at numerous nodes on a phylogeny while
integrating over uncertainty in the phylogenyetic and the model of
character change uncertainty; and provides discrete-time simulation
functions for visualizing analysis results as well as a priori models.
Availability: MaATiICCE is open source and written entirely in R
language. Source and compiled binaries are freely available through RForge ( HYPERLINK "http://r-forge.r-project.org/"
http://r-forge.rproject.org/ ).
Contact:
HYPERLINK "mailto:ahipp@mortonarb.org"
ahipp@mortonarb.org
INTRODUCTION
Inferring the evolutionary history of species traits is a basic
fundamental problem in evolutionary biology and an issue of practical
concern for ecologists, developmental biologists, and others testing
biological hypotheses using phylogenetic data. Methods of analyzing
categorical data in a phylogenetic context have addressed the problem of
localizing character transitions to branches {Huelsenbeck, 2003 #533;Ree,
2005 #1286;Nielsen, 2002 #535}. Transitions New methods utilizing
phylogenetic generalized least squares model shifts in inthe dynamics of
continuous character evolutions {Revell, 2009 #1444;O'Meara, 2006
#813;Scales, 2009 #1469;Butler, 2004 #598}. XXX. have received less
focus, despite the fact that among-clade differences in character
distributions often reflect a biologically interesting process (shifts in
environment, changes in evolutionary dynamics or population-level
processes, etc.). Alternatives to the constant variance model (Brownian
Motion model) of continuous character evolution have until recently
focused primarily on branch-length transformations that model how
different evolutionary scenarios affect phylogenetic structure and the
mode and tempo of evolution {Pagel, 1999 #432;Blomberg, 2003
#1312;O'Meara, 2006 #813}. These methods, however, are not generally
useful for identifying (1) whether an apparent change in the distribution
of a character on a tree is significant enough to warrant further
investigation, (2) whether the particular distribution tells us something
about the evolution of this trait, and (3) where on the phylogeny this
change in distribution took place.
Evaluating alternative Ornstein-Uhlenbeck (O-U) models in a phylogenetic
context {Butler, 2004 #598;Martins, 1997 #421;Hansen, 2008 #1277} may be
used to address such questions about evolutionary transitions in
continuous characters. The use of O-U models typically focuses on testing
adaptive scenarios {Bergmann, 2009 #1319;Smith, 2008 #1091;Verdu, 2006
#787} or phylogenetic constraints {Diniz-Filho, 2001 #987;Blomberg, 2003
#1312}. However, two recent studies {Hipp, 2007 #1051;Lumbsch, 2008
#1282} have utilized O-U models to estimate the probability of continuous
character transitions on phylogenetic trees, modeled as shifts in
character equilibrium or optimum. The approach taken entailed (1)
identifying n nodes at which a change may have occurred, (2) evaluating
support for all 2n models that allow all permutations of change at those
nodes, and (3) estimating the support for a transition in character state
at each node studied as the cumulative information criterion weight for
all models entailing a shift at that node {Burnham, 2002 #791}. The
software described in this application note—MmaatTicceCCE, a package
written in the R statistical language {R-Development-Core-Team, 2004
#588}—extends this method by allowing for phylogenetic uncertainty and
for limits on the maximum number of nodes at which transitions are
allowed to occur; implementing a set of discrete-time simulations for
visualization of character evolution under different models; providing an
easy interface by which to test numerous whole-tree and partitioned-tree
models for a particular phylogenetic branch; and allowing for flexibility
in defining nodes for analysis. The method is similar to a stepwise AIC
approach {Yamashita, 2007 #1532;Alfaro, 2009 #1509}. However, by taking a
model-averaging approach rather than a model-selection approach, it is
not susceptible to the significance threshold effects that introduce
uncertainty into model-selection.
IMPLEMENTATION
The MmatTicceCCE package (http://r-forge.rproject.org/projects/mattice/) provides functions for generating the
potentially large number of model specifications required to test
character transition hypotheses; performing and summarizing analyses over
a single tree or a set of trees, allowing analyses to be performed even
for nodes that are not found in all trees being studied; simulating and
visualizing character evolution under a user-specified model or using
model-averaged parameters from a mMatTicceCCE analysis; and evaluating
the relative support for several different character-transition models on
a single node. The approach presupposes that (1) flat priors on all
models are reasonable; (2) all nodes of interest have been specified; (3)
XXX
The likelihood calculations are all performed in ouch {Butler, 2004
#598;King, 2009 #1313}, but addressing these particular questions entails
summarizing analyses over a large number of specified models and
extracting tree data to analyze over phylogenetic uncertainty, functions
that would be superfluous in ouch.
AVAILABILITY
For more details see the vignette: vignette(‘maticce’)
Installation: install.packages("maticce", repos="http://R-Forge.Rproject.org")
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