Assessing phenotypic correlation through the multivariate phylogenetic latent liability model

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Cybis, Gabriela B., Sinsheimer, Janet S., Bedford, Trevor, Mather, Alison E., Lemey, Philippe and Suchard, Marc A. (2015) Assessing phenotypic correlation through the multivariate phylogenetic latent liability model. Annals of Applied Statistics, 9 (2). pp. 969-991. ISSN 1932-6157

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Abstract

Understanding which phenotypic traits are consistently correlated throughout evolution is a highly pertinent problem in modern evolutionary biology. Here, we propose a multivariate phylogenetic latent liability model for assessing the correlation between multiple types of data, while simultaneously controlling for their unknown shared evolutionary history informed through molecular sequences. The latent formulation enables us to consider in a single model combinations of continuous traits, discrete binary traits and discrete traits with multiple ordered and unordered states. Previous approaches have entertained a single data type generally along a fixed history, precluding estimation of correlation between traits and ignoring uncertainty in the history. We implement our model in a Bayesian phylogenetic framework, and discuss inference techniques for hypothesis testing. Finally, we showcase the method through applications to columbine flower morphology, antibiotic resistance in Salmonella and epitope evolution in influenza.

Item Type:	Article
Faculty \ School:
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
Related URLs:	http://projecteuclid.org/euclid.aoas/143...
Depositing User:	LivePure Connector
Date Deposited:	24 Apr 2019 11:30
Last Modified:	06 Jun 2024 15:06
URI:	https://ueaeprints.uea.ac.uk/id/eprint/70666
DOI:	10.1214/15-AOAS821

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