![]() The parameters of the model are not intended to be interpreted literally-they are simply tools to help visualize the relationship of genes to geography. Importantly, it is a model-based visualization tool. EEMS uses a model based on local “effective migration” and “diversity” parameters. One of these methods is the tool EEMS (for Estimated Effective Migration Surfaces, Petkova et al. 2018 House and Hahn 2018 Ringbauer et al. 2016 Novembre and Peter 2016 Ringbauer et al. Since those early studies, methods in spatial or landscape genetics have matured, with new, powerful methods capable of modeling population structure allowing for spatial heterogeneity ( Guillot et al. 2002) observed broad geographic clustering, which lead to a debate whether human fine-scale genetic variation is better characterized by discrete clusters or continuous clines ( Serre and Pääbo 2004 Rosenberg et al. Later studies of large microsatellite marker panels ( Rosenberg et al. 1994), mostly across Europe, found that some allele frequencies exhibit zones of elevated change that frequently align with each other. Pioneering studies of classical blood group and allozyme loci ( Barbujani and Sokal 1990 Cavalli-Sforza et al. 2019) However, due to the complexities of geography and history, this relationship varies across the globe. 2012 Bradburd and Ralph 2019 Battey et al. In many regions of the world, human genetic diversity “mirrors” geography in the sense that genetic differentiation increases with geographic distance (“isolation by distance” Ramachandran et al. Population structure, population genetics, human genetics, isolation-by-distance, geography, geographic structure Overall, the visualizations provide a new perspective on genetics and geography in humans and insight to the geographic distribution of human genetic variation. The results reveal local patterns of differentiation in detail and emphasize that while genetic similarity generally decays with geographic distance, the relationship is often subtly distorted. Here, we estimate “effective migration” surfaces to visualize how human genetic diversity is geographically structured. However, most analytical methods to represent population structure do not incorporate geography directly, and it must be considered post hoc alongside a visual summary of the genetic structure. ![]() Summarizing and visually representing these patterns of diversity has been a persistent goal for human geneticists, and has revealed that genetic differentiation is frequently correlated with geographic distance. Geographic patterns in human genetic diversity carry footprints of population history and provide insights for genetic medicine and its application across human populations.
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