Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel's lambda model

Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model | bioRxiv Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model Zheng-Lin Chen , Hong-Ji Guo , View ORCID Profile Deng-Ke Niu doi: https://doi.org/10.1101/2023.05.21.541623 Zheng-Lin Chen 1 MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University , Beijing, 100875, China 2 Beijing Key Laboratory of Gene Resource and Molecular Development, College of Life Sciences, Beijing Normal University , Beijing, 100875, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hong-Ji Guo 1 MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University , Beijing, 100875, China 2 Beijing Key Laboratory of Gene Resource and Molecular Development, College of Life Sciences, Beijing Normal University , Beijing, 100875, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Deng-Ke Niu 1 MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University , Beijing, 100875, China 2 Beijing Key Laboratory of Gene Resource and Molecular Development, College of Life Sciences, Beijing Normal University , Beijing, 100875, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Deng-Ke Niu For correspondence: dkniu{at}bnu.edu.cn dengkeniu{at}hotmail.com Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Phylogenetic generalized least squares (PGLS) regression is widely used to examine evolutionary associations while accounting for phylogenetic non-independence, but it requires designating one trait as the dependent variable and the other as the independent variable. When causal relationships between traits are unclear, choosing which trait serves as the dependent variable becomes a practical concern. While studying the evolutionary relationship between bacterial growth rate and CRISPR-Cas content, we noticed that switching the roles of dependent and independent variables in PGLS analyses could lead to inconsistent conclusions in a substantial proportion of cases. To confirm this observation, we conducted 16,000 simulations of trait evolution along binary trees with 100 terminal nodes under different evolutionary models. PGLS regressions using Pagel’s λ model were applied to each simulation, and the results consistently showed that swapping the dependent and independent variables can lead to inconsistent outcomes. We evaluated seven potential criteria for selecting the dependent variable, including log-likelihood, AIC, R 2 , p-value, Pagel’s λ, Blomberg’s K, and the estimated λ in the Pagel’s λ model. Among these, Pagel’s λ, Blomberg’s K, and the estimated λ performed equally well and outperformed the others in selecting the dependent variable, providing a reliable basis for PGLS analyses when causal direction between traits is unclear. Competing Interest Statement The authors have declared no competing interest. Footnotes In this revised version, we have carefully updated the manuscript to improve clarity, logical flow, and conceptual accuracy. In particular, the Introduction and Discussion sections have been substantially revised. Earlier versions contained some imprecise phrasing and conceptual ambiguities, reflecting our limited prior experience in this field at the time of writing in 2023. These sections have now been thoroughly reworked to clearly articulate the motivation for the study, the practical challenges in PGLS regression when causal relationships are unclear, and the significance of selecting the dependent variable based on phylogenetic signal. The Abstract has also been revised to align with these improvements, emphasizing the key findings in both empirical data and extensive simulations without overemphasizing technical details. Funder Information Declared National Natural Science Foundation of China , 31671321 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license . Back to top Previous Next Posted March 18, 2026. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model Zheng-Lin Chen , Hong-Ji Guo , Deng-Ke Niu bioRxiv 2023.05.21.541623; doi: https://doi.org/10.1101/2023.05.21.541623 Share This Article: Copy Citation Tools Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model Zheng-Lin Chen , Hong-Ji Guo , Deng-Ke Niu bioRxiv 2023.05.21.541623; doi: https://doi.org/10.1101/2023.05.21.541623 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Evolutionary Biology Subject Areas All Articles Animal Behavior and Cognition (8003) Biochemistry (18709) Bioengineering (14841) Bioinformatics (44364) Biophysics (22561) Cancer Biology (19682) Cell Biology (26845) Clinical Trials (138) Developmental Biology (13943) Ecology (20970) Epidemiology (2067) Evolutionary Biology (25415) Genetics (16151) Genomics (23478) Immunology (18681) Microbiology (42421) Molecular Biology (18022) Neuroscience (93355) Paleontology (699) Pathology (2977) Pharmacology and Toxicology (5086) Physiology (8105) Plant Biology (15969) Scientific Communication and Education (2094) Synthetic Biology (4549) Systems Biology (10219) Zoology (2384)

Related documents

• MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space#6327
• bifrost: an R package for scalable inference of phylogenetic shifts in multivariate evolutionary dynamics#180135
• MrBayes 3: Bayesian phylogenetic inference under mixed models#6315
• WitChi: Efficient Detection and Pruning of Compositional Bias in Phylogenomic Alignments Using Empirical Chi-Squared Testing#361556
• Leveraging genetic time series data to improve detection of natural selection#964173