Testing for phylogenetic signal in phenotypic traits: new matrices of phylogenetic proximities.

Theor Popul Biol

Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université de Lyon, Université Lyon 1, France.

Published: February 2008

AI Article Synopsis

  • Abouheif developed a test for detecting phylogenetic signals in traits using a modified Moran's I statistic and introduced two new matrices of phylogenetic proximities (matrix A and matrix M).
  • Matrix A integrates methods from Abouheif, Moran, and Geary, while matrix M is relevant for biodiversity studies, improving the analysis of phylogenetic autocorrelation.
  • Simulations show that matrices A and M offer better power and reduced type-I error compared to common phylogenetic proximity matrices, making them effective for analyzing unresolved phylogenetic trees; data and methods are available online.

Article Abstract

Abouheif adapted a test for serial independence to detect a phylogenetic signal in phenotypic traits. We provide the exact analytic value of this test, revealing that it uses Moran's I statistic with a new matrix of phylogenetic proximities. We introduce then two new matrices of phylogenetic proximities highlighting their mathematical properties: matrix A which is used in Abouheif test and matrix M which is related to A and biodiversity studies. Matrix A unifies the tests developed by Abouheif, Moran and Geary. We discuss the advantages of matrices A and M over three widely used phylogenetic proximity matrices through simulations evaluating power and type-I error of tests for phylogenetic autocorrelation. We conclude that A enhances the power of Moran's test and is useful for unresolved trees. Data sets and routines are freely available in an online package and explained in an online supplementary file.

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http://dx.doi.org/10.1016/j.tpb.2007.10.001DOI Listing

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