ArticleeLife2021
Fast and flexible estimation of effective migration surfaces.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
49 citing papers in PubMed.
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- Natural and Anthropogenic Drivers of Genomic Diversity in the California Towhee: Conservation Implications for Peripheral Populations.Evolutionary applications · 2026Article
- Within-Island Diversification Generates Lineage-Specific Climate Vulnerability: Insights From the Taiwan-Endemic Formosan Duke.Evolutionary applications · 2026Article
- Large-Scale Genomics Reveals Three-Source Ancestry and Layered Adaptation to High Altitude in Tibetan Chickens.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- FRAME: Fine-Resolution Asymmetric Migration Estimation.Nature communications · 2026Article
- Population Structure of the Jewel Scarab Chrysina gloriosa.Genome biology and evolution · 2026Article
- Conservation Units for Anadromous Arctic Char (Evolutionary applications · 2026Article
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- A Beginner's How-To Guide to Urban Population Genetics and Genomics.Ecology and evolution · 2026Review
- Network-based genetic monitoring of landscape fragmentation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The Source-Sink Dynamics of Plasmodium vivax May Undermine Malaria Elimination Efforts in the Amazon: An Epidemiological and Population Genomic Study.The Journal of infectious diseases · 2026Article
- Integrating mosquito genomics into simulation modeling: opportunities for better-informed biocontrol.Current opinion in insect science · 2026Review
- Joint test of historical vs. contemporary biogeography supports abundant center hypothesis shaping spatial patterns of self-fertilization.Evolution letters · 2026Article
- Continent-wide view of genomic diversity and divergence in the wolves of Asia.Communications biology · 2025Article
- Local Selection Shaped the Diversity of European Maize Landraces.Molecular ecology · 2025Article
- Dynamic human admixture histories over the past ~1300 years at the northern Himalayan frontier.Science advances · 2025Article
- When migration leaves a clean trace: Decoupling migration from coalescence in the structured serial coalescent.bioRxiv : the preprint server for biology · 2025Article
- Genetic and Landscape Connectivity of Blacklegged Ticks During Range Expansion in Select States of the Midwestern USA.Ecology and evolution · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Spatial population genetic data often exhibits 'isolation-by-distance,' where genetic similarity tends to decrease as individuals become more geographically distant. The rate at which genetic similarity decays with distance is often spatially heterogeneous due to variable population processes like genetic drift, gene flow, and natural selection. Petkova et al., 2016 developed a statistical method called Estimating Effective Migration Surfaces (EEMS) for visualizing spatially heterogeneous isolation-by-distance on a geographic map. While EEMS is a powerful tool for depicting spatial population structure, it can suffer from slow runtimes. Here, we develop a related method called Fast Estimation of Effective Migration Surfaces (FEEMS). FEEMS uses a Gaussian Markov Random Field model in a penalized likelihood framework that allows for efficient optimization and output of effective migration surfaces. Further, the efficient optimization facilitates the inference of migration parameters per edge in the graph, rather than per node (as in EEMS). With simulations, we show conditions under which FEEMS can accurately recover effective migration surfaces with complex gene-flow histories, including those with anisotropy. We apply FEEMS to population genetic data from North American gray wolves and show it performs favorably in comparison to EEMS, with solutions obtained orders of magnitude faster. Overall, FEEMS expands the ability of users to quickly visualize and interpret spatial structure in their data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.