multiModel: Test multiple models of character transition at a single node
In maticce: Mapping Transitions in Continuous Character Evolution

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Compares up to five different models of character evolution: two models of no transition (Brownian motion and a single- optimum Ornstein-Uhlenbeck model); one model allowing transition at a single node in a whole-tree context; and two models that split the tree into two subtrees and treat character evolution separately in the two trees (the ‘censored’ approach – see discussion below).

1 2	multiModel(phy, dat, node, models = c("whole.brown", "whole.ou1", "whole.ou2", "part.brown", "part.ou"))

`phy`	An ape-style tree
`dat`	A vector of data, with names corresponding to tips in `phy`
`node`	A single node, defined by the tips that are descendent from it
`models`	The vector of models, where “whole” indicates a model in which the tree is treated as a single entity, and “part” indicates a model in which the tree is subdivided and treated as two entities

This function is useful after you have identified nodes at which significant character transitions are likely to have occurred. Its use is to identify whether shifts at a given node are compatible with a single Ornstein-Uhlenbeck (O-U) model with a change in equilibrium value at the node; a two-tree model, with each tree evolving under a separate Brownian motion or O-U model; or a no-change model, either Brownian motion or no-change O-U model. Details and discussion of biological interpretation of these models is in Hipp 2007.

A list with two items:

`IC`	A matrix of information criterion statistics, generated by `informationCriterion`
`modelMatrix`	A matrix of model parameters for the whole-tree models, the partial-trees models, and summed-partial-trees models

In ouch version 2.x, the ouchtree function rescales trees to depth = 1. The alpha and sigma parameters are thus not directly comparable between subtrees, as they were in previous versions of ouch, and this function as currently implemented should not be used to test for shifts in evolutionary rate within a tree (cf. O'Meara et al. 2006). Such a test can be performed in geiger, an R package, or brownie, which is available as a stand-alone application or a set of MATLAB modules.

Andrew L. Hipp ahipp@mortonarb.org

Hipp, A.L. (2007) Non-uniform processes of chromosome evolution in sedges (Carex: Cyperaceae). Evolution 61:2175–2194.

O'Meara, B. C., C. Ane, M. J. Sanderson, and P. C. Wainwright (2006) Testing for different rates of continuous trait evolution using likelihood. Evolution 60:922–933.

O'Meara, B. C. (2009) brownie v 1.0 (MATLAB) and v 2.0 (stand-alone). http://www.brianomeara.info/brownie/

carex for an example

  library(maticce)
  data(carex)
  attach(carex)
  # compare five different models of character change at node 2:
  mm2 <- multiModel(carex$ovales.tree, ovales.data, ovales.nodes[[2]]) 
  mm2
  layout(matrix(1:4,2,2))
  pie(mm2$IC$AICwi, labels = mm2$IC$name, col = rainbow(length(mm2$IC$name)), main="AIC weights")
  pie(mm2$IC$AICcwi, labels = mm2$IC$name, col = rainbow(length(mm2$IC$name)), main="AICc weights")
  pie(mm2$IC$BICwi, labels = mm2$IC$name, col = rainbow(length(mm2$IC$name)), main="BIC weights")
  noChangeAICwi <- sum(mm2$IC$AICwi[1:2])
  changeAICwi <- sum(mm2$IC$AICwi[3:5])
  barplot(c(noChangeAICwi, changeAICwi), ylim = c(0,1), 
          names.arg = c('no transition', 'transition'), main = 'Transition vs. no-transition')