qpAdm is a statistical tool that is often used for testing large sets of alternative admixture models for a target population. Despite its popularity, qpAdm remains untested on two-dimensional stepping-stone landscapes and in situations with low pre-study odds (low ratio of true to false models). We tested high-throughput qpAdm protocols with typical properties such as number of source combinations per target, model complexity, model feasibility criteria, etc. Those protocols were applied to admixture-graph-shaped and stepping-stone simulated histories sampled randomly or systematically. We demonstrate that false discovery rates of high-throughput qpAdm protocols exceed 50% for many parameter combinations since: 1) pre-study odds are low and fall rapidly with increasing model complexity; 2) complex migration networks violate the assumptions of the method, hence there is poor correlation between qpAdm p-values and model optimality, contributing to low but non-zero false positive rate and low power; 3) although admixture fraction estimates between 0 and 1 are largely restricted to symmetric configurations of sources around a target, a small fraction of asymmetric highly non-optimal models have estimates in the same interval, contributing to the false positive rate. We also re-interpret large sets of qpAdm models from two studies in terms of source-target distance and symmetry and suggest improvements to qpAdm protocols: 1) temporal stratification of targets and proxy sources in the case of admixture-graph-shaped histories; 2) focused exploration of few models for increasing pre-study odds; 3) dense landscape sampling for increasing power and stringent conditions on estimated admixture fractions for decreasing the false positive rate.

Department of Biological Sciences Middle East Technical University Üniversiteler Mahallesi Dumlupınar Bulvarı No 1 06800 Çankaya Ankara Türkiye

Department of Biology and Ecology Faculty of Science University of Ostrava Chittussiho 1077 10 710 00 Ostrava Czechia

Department of Biology Eberly College of Science The Pennsylvania State University 168 Curtin Road University Park PA 16802 USA

Department of Human Evolutionary Biology Harvard University 11 Divinity Avenue Cambridge MA 02138 USA

Institute of Parasitology Biology Centre of the Czech Academy of Sciences Branišovská 1160 31 370 05 České Budějovice Czechia

Leibniz Institute on Aging Fritz Lipmann Institute Beutenbergstraße 11 07745 Jena Germany

bioRxiv. 2025 Feb 03:2023.04.25.538339. doi: 10.1101/2023.04.25.538339. PubMed

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