DOI: 10.5061/dryad.g4t8c
title: Data from: Evolutionary rates for multivariate traits: the role of selection and genetic variation

description: A fundamental question in evolutionary biology is the relative importance
 of selection and genetic architecture in determining evolutionary rates.
 Adaptive evolution can be described by the multivariate breeders'
 equation, which predicts evolutionary change for a suite of phenotypic
 traits as a product of directional selection acting on them (β) and the
 genetic variance–covariance matrix for those traits (G). Despite being
 empirically challenging to estimate, there are enough published estimates
 of G and β to allow for synthesis of general patterns across species. We
 use published estimates to test the hypotheses that there are systematic
 differences in the rate of evolution among trait types, and that these
 differences are, in part, due to genetic architecture. We find some
 evidence that sexually selected traits exhibit faster rates of evolution
 compared with life-history or morphological traits. This difference does
 not appear to be related to stronger selection on sexually selected
 traits. Using numerous proposed approaches to quantifying the shape, size
 and structure of G, we examine how these parameters relate to one another,
 and how they vary among taxonomic and trait groupings. Despite
 considerable variation, they do not explain the observed differences in
 evolutionary rates.
description: Evolutionary rates for
 multivariate traits: the database.This is the repository
 for the `R` Code and Data for Pitchers et. al. 2014 soon to be published
 (July 2014) a special issue (Evolutionary Quantitative Genetics) of
 Philosophical Transactions of the Royal Society. We currently have a
 pre-print of a version of the manuscript on biorxiv
 (http://biorxiv.org/content/early/2014/05/05/002683). In addition to all
 of the code and data being here allowing you to reproduce all of the
 results from the paper (up to the limits of MCMC anyways), it also
 contains the database we generated on genetic covariance and correlation
 matrices that we hope will be of broad use to the Evolutionary
 Quantitative Genetics community. Here is a short guide to navigate this
 folder: 1. For the analyses of evolutionary potential using measures
 extracted from empirical **G** matrices, you can
 [review](https://github.com/DworkinLab/Pitchers_PTRS2014/blob/master/Scripts/gmax_analysis.md) or reproduce our analyses. You can also download the gmax_analysis.R file to rerun it on your local machine. This folder also contains the gmax_analysis.Rmd file in case you prefer starting with the markdown + `R` code and want to use knitr. 2. If you are interested in the analyses we performed examining rates of evolution or estimates of selection, these can also be found in the script folder, with the overview of the analysis and results here in the markdown file. 3. If you just interested in the data for your own analyses, please find it in the data subfolder. Inside you will see additional sub-folders which contain small text files for each matrix as spelled out in the name.md file mentioned above. You can also use some of the `R` code we have set-up above, to extract the databases directly into R with the `.R` objects in that folder.Pitchers_PTRS2014-master.zip