CRP-Tree: A phylogenetic association test for binary traits

TL;DR

This paper introduces CRP-Tree, a new phylogenetic association test for binary traits that models trait evolution with a Chinese Restaurant Process-inspired model, offering improved power over existing methods.

Contribution

The paper presents a novel phylogenetic association test based on a Chinese Restaurant Process model, with linear computational complexity and demonstrated effectiveness.

Findings

The test is more powerful than some existing methods.

It successfully identifies trait associations in diverse biological datasets.

The method is implemented in an R package available online.

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 $\texttt{https://github.com/jyzhang27/CRPTree}$.