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

Date

2025-05-01

Author

Flegontova, Olga
Işlldak, Ulaş
Yüncü, Eren
Williams, Matthew P.
Huber, Christian D.
Kočí, Jan
Vyazov, Leonid A.
Changmai, Piya
Flegontov, Pavel

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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 2D stepping stone landscapes and in situations with low prestudy 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) prestudy 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 nonzero false-positive rate and low power; and (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 nonoptimal models have estimates in the same interval, contributing to the false-positive rate. We also reinterpret large sets of qpAdm models from 2 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 prestudy odds; and (3) dense landscape sampling for increasing power and stringent conditions on estimated admixture fractions for decreasing the false-positive rate.

Subject Keywords

admixture graphs, archaeogenetics, genetic admixture, qpAdm, simulation, stepping stone models

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105004773080&origin=inward
https://hdl.handle.net/11511/114763

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Department of Biology, Article