ArticleGenetics2011
An accurate sequentially Markov conditional sampling distribution for the coalescent with recombination.
Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Recent advances in methods to characterize archaic introgression in modern humans.Genome research · 2026Review
- Likelihoods for a general class of ARGs under the SMC.Genetics · 2026Article
- Not Just Ne Ne-More: New Applications for SMC from Ecology to Phylogenies.Genome biology and evolution · 2026Review
- Robust and accurate Bayesian inference of genome-wide genealogies for hundreds of genomes.Nature genetics · 2025Article
- Likelihoods for a general class of ARGs under the SMC.bioRxiv : the preprint server for biology · 2025Article
- Article
- A general and efficient representation of ancestral recombination graphs.bioRxiv : the preprint server for biology · 2024Article
- Exact Decoding of a Sequentially Markov Coalescent Model in Genetics.Journal of the American Statistical Association · 2024Article
- Properties of 2-locus genealogies and linkage disequilibrium in temporally structured samples.Genetics · 2022Article
- Variational inference using approximate likelihood under the coalescent with recombination.Genome research · 2021Article
- Why are rare variants hard to impute? Coalescent models reveal theoretical limits in existing algorithms.Genetics · 2021Article
- Creating artificial human genomes using generative neural networks.PLoS genetics · 2021Article
- Inference of population history using coalescent HMMs: review and outlook.Current opinion in genetics & development · 2018Review
- Model-based detection and analysis of introgressed Neanderthal ancestry in modern humans.Molecular ecology · 2018Article
- Computing the joint distribution of the total tree length across loci in populations with variable size.Theoretical population biology · 2017Article
- Article
- Robust and scalable inference of population history from hundreds of unphased whole genomes.Nature genetics · 2017Article
- Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data.Systematic biology · 2017Review
- Article
- Coalescent Inference Using Serially Sampled, High-Throughput Sequencing Data from Intrahost HIV Infection.Genetics · 2016Article
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3 authors.
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Abstract
The sequentially Markov coalescent is a simplified genealogical process that aims to capture the essential features of the full coalescent model with recombination, while being scalable in the number of loci. In this article, the sequentially Markov framework is applied to the conditional sampling distribution (CSD), which is at the core of many statistical tools for population genetic analyses. Briefly, the CSD describes the probability that an additionally sampled DNA sequence is of a certain type, given that a collection of sequences has already been observed. A hidden Markov model (HMM) formulation of the sequentially Markov CSD is developed here, yielding an algorithm with time complexity linear in both the number of loci and the number of haplotypes. This work provides a highly accurate, practical approximation to a recently introduced CSD derived from the diffusion process associated with the coalescent with recombination. It is empirically demonstrated that the improvement in accuracy of the new CSD over previously proposed HMM-based CSDs increases substantially with the number of loci. The framework presented here can be adopted in a wide range of applications in population genetics, including imputing missing sequence data, estimating recombination rates, and inferring human colonization history.
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