CRP-Tree: a phylogenetic association test for binary traits

Author:

Zhang Julie1ORCID,Preising Gabriel A2,Schumer Molly2ORCID,Palacios Julia A13

Affiliation:

1. Department of Statistics, Stanford University , Stanford, CA , USA

2. Department of Biology, Stanford University , Stanford, CA , USA

3. Department of Biomedical Data Science, Stanford University , Stanford, CA , USA

Abstract

Abstract An important problem in evolutionary genomics is to investigate whether a certain trait measured on each sample is associated with the sample phylogenetic tree. The phylogenetic tree represents the shared evolutionary history of the samples and it is usually estimated from molecular sequence data at a locus or from other type of genetic data. We propose a model for trait evolution inspired by the Chinese Restaurant Process that includes a parameter that controls the degree of preferential attachment, that is, the tendency of nodes in the tree to subtend from nodes of the same type. This model with no preferential attachment is equivalent to a structured coalescent model with simultaneous migration and coalescence events and serves as a null model. We derive a test for phylogenetic binary trait association with linear computational complexity and empirically demonstrate that it is more powerful than some other methods. We apply our test to study the phylogenetic association of some traits in swordtail fish, breast cancer, yellow fever virus, and influenza A H1N1 virus. R-package implementation of our methods is available at https://github.com/jyzhang27/CRPTree.

Funder

National Science Foundation

Sloan Fellowship

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference62 articles.

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3. Testing for dependence on tree structures;Behr;PNAS,2020

4. Testing for phylogenetic signal in comparative data: Behavioral traits are more labile;Blomberg;Evolution,2003

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