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iteRates: An R Package for Implementing a Parametric Rate Comparison on Phylogenetic Trees.

Fordyce JA, Shah P, Fitzpatrick BM - Evol. Bioinform. Online (2014)

Bottom Line: Patterns of diversification rate variation detected in phylogenetic hypotheses are frequently used to infer historical, ecological, and evolutionary processes.The parametric rate comparison (PRC) is a method for detecting rate variation in trees that models branch lengths as random variables drawn from familiar statistical distributions. iteRates is a library of functions for the R statistical computing environment for implementing PRC on phylogenetic trees.Here, we describe some of the functions in iteRates for subtree identification, tree manipulation, applying the PRC and K-clades PRC analyses, and conducting a whole-tree randomization test.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA. ; National Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA.

ABSTRACT
Patterns of diversification rate variation detected in phylogenetic hypotheses are frequently used to infer historical, ecological, and evolutionary processes. The parametric rate comparison (PRC) is a method for detecting rate variation in trees that models branch lengths as random variables drawn from familiar statistical distributions. iteRates is a library of functions for the R statistical computing environment for implementing PRC on phylogenetic trees. Here, we describe some of the functions in iteRates for subtree identification, tree manipulation, applying the PRC and K-clades PRC analyses, and conducting a whole-tree randomization test.

No MeSH data available.


A phylogenetic tree showing the subtrees identified by the function id.subtrees. For the example in the text, the subtrees defined by nodes 55, 27, and 3 make up the three groups examined using the K-clades PRC, identified by the argument focal = c(55,27,3) in the function comp.fit.subs.
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f2-ebo-10-2014-127: A phylogenetic tree showing the subtrees identified by the function id.subtrees. For the example in the text, the subtrees defined by nodes 55, 27, and 3 make up the three groups examined using the K-clades PRC, identified by the argument focal = c(55,27,3) in the function comp.fit.subs.

Mentions: Here, tree.Kclades$subtree is the list of all subtrees provided by id.subtrees. The argument focal indicates the identifier of the subtrees of interest for comparison. Figure 2 shows a hypothetical phylogenetic tree with the subtrees of interest indicated. The argument k indicates the maximum number of different rates to explore, in this case three. The function will compare all possible models of rate variation, ranging from all subtrees having the same rate, to k number of subtrees having different rates. As in the function comp.subs, the user can choose any combination of the four available statistical distributions using the argument mod.id. The default is to fit only an exponential distribution (mod. id = c(1,0,0,0)). Parameter values, log likelihood, and AIC scores and ΔAIC are returned. The results can be summarized using the function tab.summary, which will restrict the returned output to a ΔAIC limit determined by the user and the best-fit model for each k. An example of tab.summary and output is as follows:


iteRates: An R Package for Implementing a Parametric Rate Comparison on Phylogenetic Trees.

Fordyce JA, Shah P, Fitzpatrick BM - Evol. Bioinform. Online (2014)

A phylogenetic tree showing the subtrees identified by the function id.subtrees. For the example in the text, the subtrees defined by nodes 55, 27, and 3 make up the three groups examined using the K-clades PRC, identified by the argument focal = c(55,27,3) in the function comp.fit.subs.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4125422&req=5

f2-ebo-10-2014-127: A phylogenetic tree showing the subtrees identified by the function id.subtrees. For the example in the text, the subtrees defined by nodes 55, 27, and 3 make up the three groups examined using the K-clades PRC, identified by the argument focal = c(55,27,3) in the function comp.fit.subs.
Mentions: Here, tree.Kclades$subtree is the list of all subtrees provided by id.subtrees. The argument focal indicates the identifier of the subtrees of interest for comparison. Figure 2 shows a hypothetical phylogenetic tree with the subtrees of interest indicated. The argument k indicates the maximum number of different rates to explore, in this case three. The function will compare all possible models of rate variation, ranging from all subtrees having the same rate, to k number of subtrees having different rates. As in the function comp.subs, the user can choose any combination of the four available statistical distributions using the argument mod.id. The default is to fit only an exponential distribution (mod. id = c(1,0,0,0)). Parameter values, log likelihood, and AIC scores and ΔAIC are returned. The results can be summarized using the function tab.summary, which will restrict the returned output to a ΔAIC limit determined by the user and the best-fit model for each k. An example of tab.summary and output is as follows:

Bottom Line: Patterns of diversification rate variation detected in phylogenetic hypotheses are frequently used to infer historical, ecological, and evolutionary processes.The parametric rate comparison (PRC) is a method for detecting rate variation in trees that models branch lengths as random variables drawn from familiar statistical distributions. iteRates is a library of functions for the R statistical computing environment for implementing PRC on phylogenetic trees.Here, we describe some of the functions in iteRates for subtree identification, tree manipulation, applying the PRC and K-clades PRC analyses, and conducting a whole-tree randomization test.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA. ; National Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA.

ABSTRACT
Patterns of diversification rate variation detected in phylogenetic hypotheses are frequently used to infer historical, ecological, and evolutionary processes. The parametric rate comparison (PRC) is a method for detecting rate variation in trees that models branch lengths as random variables drawn from familiar statistical distributions. iteRates is a library of functions for the R statistical computing environment for implementing PRC on phylogenetic trees. Here, we describe some of the functions in iteRates for subtree identification, tree manipulation, applying the PRC and K-clades PRC analyses, and conducting a whole-tree randomization test.

No MeSH data available.