Phenotypic sequences are a type of multivariate trait organized structurally, such as teeth distributed along the dental arch, or temporally, such as the stages of an ontogenetic series. Unlike other multivariate traits, the elements of a phenotypic sequence are distributed along an ordered set, which allows for distinct evolutionary patterns between neighboring and distant positions. In fact, sequence traits share many characteristics with molecular sequences, although important distinctions pose challenges to current comparative methods. We implement an approach to estimate rates of trait evolution that explicitly incorporates the sequence organization of traits. We apply models to study the temporal pattern evolution of cricket calling songs. We test whether neighboring positions along a phenotypic sequence have correlated rates of evolution or if rate variation is independent of sequence position. Our results show that cricket song evolution is strongly autocorrelated and models perform well when used with sequence phenotypes even under small sample sizes. Our approach is flexible and can be applied to any multivariate trait with discrete units organized in a sequence-like structure.

Data was extracted from: Robillard, T., F. Legendre, L. Desutter-Grandcolas, and P. Grandcolas. 2006. Phylogenetic analysis and alignment of behavioral sequences by direct optimization. Cladistics 22:602–633.

Code to process the data is available on this repository.

Data was analyzed using custom software available at https://github.com/Caetanods/CorrSeq

September, 2019
Daniel Caetano and Jeremy Beaulieu
University of Arkansas
Department of Biological Sciences

This is the repository for our publication "Comparative analyses of phenotypic sequences using phylogenetic trees". The repository is divided into directories with the correspondent information and data.

/data: Has the song sequences in raw format and time rescaled formats. Also divided in complete sequences (the 5s recording interval) and song bouts. There are two types of song bouts - long silence bouts and short silence bouts. The difference is that short silence bouts consider only half of the interchirp silence intervals and the long bouts consider the whole interchirp silence interval. Short bouts were introduced by the suggestion of the reviewers. See main text and supplementary material for more information.

/empirical_analysis: Has the scripts and results for the sequence alignment and model fit to the data. These are subdivided into treatments following the same rationale described on the manuscript.

/manuscript_figures: Information for the figures used in the main text of the manuscript.

/phylogeny: Has the molecular alignment, BEAST xml files and the MCC tree used in this study.

/simulations: The scripts and results for simulations.

/tutorial_analyses: An script showing how to use the resources of the R package.

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The software used to conduct the analyses is available on github.

We used an machine with Ubuntu Linux version 18.04.2 LTS

The programming language was: R version 3.6.0 (2019-04-26) -- "Planting of a Tree"

The link to the package repository: https://github.com/Caetanods/CorrSeq

You can install the package from the github repository using the function:
devtools::install_github("Caetanods/CorrSeq")

Dependencies of the package (as of Sept, 2019):

Rcpp::sourceCpp
ape::Ntip
ape::reorder.phylo
expm::expm
nloptr::nloptr
pbivnorm::pbivnorm

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If reusing this data, please cite: Robillard, T., F. Legendre, L. Desutter-Grandcolas, and P. Grandcolas. 2006. Phylogenetic analysis and alignment of behavioral sequences by direct optimization. Cladistics 22:602–633.