ArticleGenome research2023
Ultrafast genome-wide inference of pairwise coalescence times.
Article in Genome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Fast pairwise coalescence enables gene-resolution scans for recent selection in diverse human populations.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
- Polarising SNPs Without Outgroup.Molecular ecology resources · 2026Article
- Clade distillation for genome-wide association studies.Genetics · 2026Article
- Not Just Ne Ne-More: New Applications for SMC from Ecology to Phylogenies.Genome biology and evolution · 2026Review
- Accessible, Realistic Genome Simulation with Selection Using stdpopsim.Molecular biology and evolution · 2025Article
- Robust and accurate Bayesian inference of genome-wide genealogies for hundreds of genomes.Nature genetics · 2025Article
- Accessible, realistic genome simulation with selection using stdpopsim.bioRxiv : the preprint server for biology · 2025Article
- Article
- Rapid Adaptation and Interspecific Introgression in the North American Crop Pest Helicoverpa zea.Molecular biology and evolution · 2024Article
- Accurate inference of population history in the presence of background selection.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The pairwise sequentially Markovian coalescent (PSMC) algorithm and its extensions infer the coalescence time of two homologous chromosomes at each genomic position. This inference is used in reconstructing demographic histories, detecting selection signatures, studying genome-wide associations, constructing ancestral recombination graphs, and more. Inference of coalescence times between each pair of haplotypes in a large data set is of great interest, as they may provide rich information about the population structure and history of the sample. Here, we introduce a new method,
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