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

Authors :
Diego S. Porto
Sergei Tarasov
Caleb Charpentier
Hilmar Lapp
James P. Balhoff
Todd J. Vision
Wasila M. Dahdul
Paula M. Mabee
Josef Uyeda
Source :
Methods in Ecology and Evolution, Vol 14, Iss 10, Pp 2531-2540 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

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.

Details

Language :
English
ISSN :
2041210X
Volume :
14
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Methods in Ecology and Evolution
Publication Type :
Academic Journal
Accession number :
edsdoj.72466f9aa8764788ad1632906ee8b280
Document Type :
article
Full Text :
https://doi.org/10.1111/2041-210X.14210