A tale of too many trees: a conundrum for phylogenetic regression

系统发育树 系统发育比较方法 生物 特质 树(集合论) 树重组 进化生物学 系统发育学 生命之树(生物学) 比较法 回归 系统发育网络 生态学 计量经济学 统计 计算机科学 基因 遗传学 数学 数学分析 语言学 哲学 程序设计语言
作者
Richard H. Adams,Jenniffer Roa Lozano,Mataya Duncan,Jack E. Green,Raquel Assis,Michael DeGiorgio
出处
期刊:Molecular Biology and Evolution [Oxford University Press]
标识
DOI:10.1093/molbev/msaf032
摘要

Abstract Just exactly which tree(s) should we assume when testing evolutionary hypotheses? This question has plagued comparative biologists for decades. Though all phylogenetic comparative methods require input trees, we seldom know with certainty whether even a perfectly estimated tree (if this is possible in practice) is appropriate for our studied traits. Yet, we also know that phylogenetic conflict is ubiquitous in modern comparative biology, and we are still learning about its dangers when testing evolutionary hypotheses. Here we investigate the consequences of tree-trait mismatch for phylogenetic regression in the presence of gene tree-species tree conflict. Our simulation experiments reveal excessively high false positive rates for mismatched models with both small and large trees, simple and complex traits, and known and estimated phylogenies. In some cases, we find evidence of a directionality of error: assuming a species tree for traits that evolved according to a gene tree sometimes fares worse than the opposite. We also explored the impacts of tree choice using an expansive, cross-species gene expression dataset as an arguably “best-case” scenario in which one may have a better chance of matching tree with trait. Offering a potential path forward, we found promise in the application of a robust estimator as a potential, albeit imperfect, solution to some issues raised by tree mismatch. Collectively, our results emphasize the importance of careful study design for comparative methods, highlighting the need to fully appreciate the role of accurate and thoughtful phylogenetic modeling.
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