ArticleNature genetics2025
Robust and accurate Bayesian inference of genome-wide genealogies for hundreds of genomes.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Genomic insights into natural selection in recent human history.Nature reviews. Genetics · 2026Review
- Comparing ARG Inference Methods Under Transmission of Reproductive Success: Tree Imbalance Matters.Genome biology and evolution · 2026Article
- ARGformer: learning on ancestral recombination graphs with transformers.Bioinformatics (Oxford, England) · 2026Article
- What has population genomics told us about the dynamics of selection and plant adaptation?Molecular biology and evolution · 2026Review
- The rights and wrongs of rescaling in population genetics simulations.PLoS genetics · 2026Review
- ERICA-trio: an outgroup-free deep learning method for topology inference and introgression detection.Briefings in bioinformatics · 2026Article
- ARGscape: a modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs.Bioinformatics (Oxford, England) · 2026Article
- Inference of elevated mutation rates and variant effects using 700k exomes.bioRxiv : the preprint server for biology · 2026Article
- Genetic prediction with ARG-powered linear algebra.Genetics · 2026Article
- Genealogy-based trait association with LOCATER boosts power at loci with allelic heterogeneity.Genome research · 2026Article
- Highly efficient genotype compression leveraging genealogical relatedness.bioRxiv : the preprint server for biology · 2026Article
- Coalescence and translation: A language model for population genetics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Computing coalescence rates for complex demographies and sampling configurations.bioRxiv : the preprint server for biology · 2026Article
- Recovering signatures of archaic introgression using ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
- Polarising SNPs Without Outgroup.Molecular ecology resources · 2026Article
- Tracing the evolutionary histories of ultra-rare variants using variational dating of large ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
- Clade distillation for genome-wide association studies.Genetics · 2026Article
- On ARGs, pedigrees, and genetic relatedness matrices.Genetics · 2026Article
- Article
- Phantom epistasis through the lens of genealogies.Genetics · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
The Ancestral Recombination Graph (ARG), which describes the genealogical history of a sample of genomes, is a vital tool in population genomics and biomedical research. Recent advancements have substantially increased ARG reconstruction scalability, but they rely on approximations that can reduce accuracy, especially under model misspecification. Moreover, they reconstruct only a single ARG topology and cannot quantify the considerable uncertainty associated with ARG inferences. Here, to address these challenges, we introduce SINGER (sampling and inferring of genealogies with recombination), a method that accelerates ARG sampling from the posterior distribution by two orders of magnitude, enabling accurate inference and uncertainty quantification for hundreds of whole-genome sequences. Through extensive simulations, we demonstrate SINGER's enhanced accuracy and robustness to model misspecification compared to existing methods. We demonstrate the utility of SINGER by applying it to individuals of British and African descent within the 1000 Genomes Project, identifying signals of population differentiation, archaic introgression and strong support for ancient polymorphism in the human leukocyte antigen region shared across primates.
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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 Socratic graph.