Efficient moment-based inference of admixture parameters and sources of gene flow
Mark Lipson, Po-Ru Loh, Alex Levin, David Reich, Nick Patterson,, Bonnie Berger

TL;DR
MixMapper is a new, efficient method for constructing phylogenetic trees with admixture events from SNP data, automatically estimating model parameters and uncertainty, and revealing ancient gene flow in human populations.
Contribution
It introduces a two-phase moment-based approach for admixture inference that automatically estimates topology, sources, branch lengths, and proportions from genetic data.
Findings
Confirmed ancient admixture in European populations, including Sardinians and Basques.
Identified 20-40% northern Eurasian ancestry in European populations.
Successfully analyzed 30 populations, with 20 showing admixture signals.
Abstract
The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically…
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Taxonomy
TopicsForensic and Genetic Research · Genetic diversity and population structure · Genetic Associations and Epidemiology
