Performance of qpAdm -based screens for genetic admixture on admixture-graph-shaped histories and stepping-stone landscapes

作者：Olga Flegontova, Ulaş Işıldak, Eren Yüncü, Matthew P. Williams, Christian D. Huber, Ján Kočí, Leonid Vyazov, Piya Changmai, Pavel Flegontov · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2023 · DOI：10.1101/2023.04.25.538339 · 被引用次数：15 · 研究领域：Molecular Biology Techniques and Applications、Forensic and Genetic Research、Identification and Quantification in Food

Abstract 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 ...