rphenoscate: An R package for semantics‐aware evolutionary analyses of anatomical traits

Author:

Porto Diego S.12ORCID,Tarasov Sergei1ORCID,Charpentier Caleb2ORCID,Lapp Hilmar3ORCID,Balhoff James P.4ORCID,Vision Todd J.5ORCID,Dahdul Wasila M.6ORCID,Mabee Paula M.7ORCID,Uyeda Josef2ORCID

Affiliation:

1. Finnish Museum of Natural History Helsinki Finland

2. Department of Biological Sciences Virginia Tech Blacksburg Virginia USA

3. Department of Biostatistics & Bioinformatics Duke University Durham North Carolina USA

4. Renaissance Computing Institute University of North Carolina Chapel Hill North Carolina USA

5. Department of Biology and School of Information and Library Sciences University of North Carolina Chapel Hill North Carolina USA

6. UCI Libraries University of California Irvine California USA

7. Battelle, National Ecological Observatory Network Boulder Colorado USA

Abstract

Abstract Organismal anatomy is a hierarchical system of anatomical entities often imposing dependencies among multiple morphological characters. Ontologies provide a formal and computable framework for incorporating prior biological knowledge about anatomical dependencies in models of trait evolution. They also offer new opportunities for working with semantic representations of morphological data. In this work, we present a new R package—rphenoscate—that enables incorporating ontological knowledge in evolutionary analyses and exploring semantic patterns of morphological data. In conjunction with rphenoscape, it allows for assembling synthetic phylogenetic character matrices from semantic phenotypes of morphological data. We showcase the package functionality with data sets from bees and fishes. We demonstrate that ontologies can be employed to automatically set up evolutionary models accounting for trait dependencies in stochastic character mapping. We also demonstrate how ontology annotations can be explored to interrogate patterns of morphological evolution. Finally, we demonstrate that synthetic character matrices assembled from semantic phenotypes retain most of the phylogenetic information from their original data sets. Ontologies will become important tools for integrating anatomical knowledge into phylogenetic methods and making morphological data FAIR compliant—a critical step of the ongoing ‘phenomics’ revolution. Our new package offers key advancements towards this goal.

Funder

Academy of Finland

National Science Foundation

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

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