ArticleAmerican journal of human genetics2025
Estimation of demography and mutation rates from one million haploid genomes.
Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Article
- Evolution of quantitative traits with background selection.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Inference of elevated mutation rates and variant effects using 700k exomes.bioRxiv : the preprint server for biology · 2026Article
- Sequence context and methylation interact to shape germline mutation rate variation at CpG sites.PLoS genetics · 2026Article
- A sibling study of variation in parental mutation rates.bioRxiv : the preprint server for biology · 2026Article
- Sequence context and methylation interact to shape germline mutation rate variation at CpG sites.bioRxiv : the preprint server for biology · 2026Article
- Evolution of the rate, molecular spectrum, and fitness effects of mutation under minimal selection in Caenorhabditis elegans.Genetics · 2026Article
- Integrating 730,947 exome sequences with clinical literature improves gene discovery.medRxiv : the preprint server for health sciences · 2026Article
- Evolutionary dynamics under phenotypic uncertainty.bioRxiv : the preprint server for biology · 2026Article
- Evolution of the rate, molecular spectrum, and fitness effects of mutation under minimal selection inbioRxiv : the preprint server for biology · 2026Article
- The performance of genetic-constraint metrics varies significantly across the human noncoding genome.bioRxiv : the preprint server for biology · 2026Article
- Tracing the evolutionary histories of ultra-rare variants using variational dating of large ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
- Mutation-selection-drift balance models of complex diseases.Genetics · 2025Article
- Allele Frequencies at Recessive Disease Genes are Mainly Determined by Pleiotropic Effects in Heterozygotes.bioRxiv : the preprint server for biology · 2025Article
- Article
- Identifying Single-Origin Rare Variants in Population Genomic Data.Molecular biology and evolution · 2025Article
- Study design and the sampling of deleterious rare variants in biobank-scale datasets.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The distribution of highly deleterious variants across human ancestry groups.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Mutation-selection-drift balance models of complex diseases.bioRxiv : the preprint server for biology · 2025Article
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3 authors.
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Abstract
As genetic sequencing costs have plummeted, datasets with sizes previously unthinkable have begun to appear. Such datasets present opportunities to learn about evolutionary history, particularly via rare alleles that record the very recent past. However, beyond the computational challenges inherent in the analysis of many large-scale datasets, large population-genetic datasets present theoretical problems. In particular, the majority of population-genetic tools require the assumption that each mutant allele in the sample is the result of a single mutation (the "infinite-sites" assumption), which is violated in large samples. Here, we present DR EVIL, a method for estimating mutation rates and recent demographic history from very large samples. DR EVIL avoids the infinite-sites assumption by using a diffusion approximation to a branching-process model with recurrent mutation. This approach results in tractable likelihoods that are accurate for rare alleles. We show that DR EVIL performs well in simulations and apply it to rare-variant data from one million haploid samples. We identify mutation-rate heterogeneity even after accounting for trinucleotide context and methylation status. We also predict that at modern sample sizes, the alleles at most polymorphic sites with high mutation rates represent the descendants of multiple mutation events.
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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.