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Phylogenetic Trees03:21

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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The “tree of life” describes the evolution of life and the evolutionary relationships between organisms. The root of the tree is the common ancestor to all life on Earth. All other species radiate from this point, much like the branches of a tree. The numerous tips of these branches on the tree of life represent every living, or extant, species. Extinct species, which are species that no longer exist, can be found towards the center of the tree. Currently, these organisms, both...
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A Practical Guide to Phylogenetics for Nonexperts
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phylosem: A fast and simple R package for phylogenetic inference and trait imputation using phylogenetic structural

James T Thorson1, Wouter van der Bijl2

  • 1Resource Ecology and Fisheries Management, Alaska Fisheries Science Center, Seattle, Washington, USA.

Journal of Evolutionary Biology
|October 9, 2023
PubMed
Summary

A new R package, phylosem, enables comprehensive phylogenetic structural equation modeling (PSEM). This tool integrates latent variables, complex trait interdependencies, and missing data imputation for advanced evolutionary analyses.

Keywords:
Ornstein-Uhlenbeckphylogenetic comparative methodsphylogenetic trait imputationstructural equation models

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Area of Science:

  • Evolutionary Biology
  • Phylogenetics
  • Quantitative Genetics

Background:

  • Phylogenetic comparative methods (PCMs) are crucial for understanding evolutionary relationships and trait trade-offs across species.
  • Existing R packages (phylolm, phylopath, Rphylopars, sem) offer partial functionalities but cannot simultaneously address key analytical needs like latent variables, complex interdependencies, and trait prediction.

Purpose of the Study:

  • To introduce the R package `phylosem` for advanced phylogenetic structural equation modeling (PSEM).
  • To provide a unified framework that integrates latent variables, complex trait interdependencies, missing trait imputation, and phylogenetic correlations.
  • To enable the estimation of relationships as comparable slope parameters.

Main Methods:

  • Development and introduction of the `phylosem` R package for PSEM.
  • Implementation of flexible covariance transformations including Ornstein-Uhlenbeck, Pagel's-δ, and Pagel's-λ.
  • Validation by replicating a case study on plant energy budgets and comparing results with existing methods.

Main Results:

  • The `phylosem` package successfully integrates multiple analytical goals within a single framework.
  • PSEM precisely reproduces estimates and standard errors for simplified scenarios solvable by other specialized packages.
  • The package demonstrates its utility in analyzing complex trait trade-offs, as shown in the plant energy budget example.

Conclusions:

  • The `phylosem` package offers a powerful and versatile tool for advanced phylogenetic comparative analyses.
  • It overcomes limitations of previous software by enabling simultaneous estimation of complex evolutionary relationships and trait predictions.
  • This facilitates a more comprehensive understanding of trait evolution and interdependencies across species.