Journal
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 363, Issue 1512, Pages 3921-3930Publisher
ROYAL SOC
DOI: 10.1098/rstb.2008.0172
Keywords
recombination rate; recombination hotspot; linkage disequilibrium; ancestral recombination graph; Bayesian inference
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Funding
- NHGRI NIH HHS [HG01988, R01 HG001988] Funding Source: Medline
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Recently, several statistical methods for estimating fine-scale recombination rates using population samples have been developed. However, currently available methods that can be applied to large-scale data are limited to approximated likelihoods. Here, we developed a full-likelihood Markov chain Monte Carlo method for estimating recombination rate under a Bayesian framework. Genealogies underlying a sampling of chromosomes are effectively modelled by using marginal individual single nucleotide polymorphism genealogies related through an ancestral recombination graph. The method is compared with two existing composite-likelihood methods using simulated data. Simulation studies show that our method performs well for different simulation scenarios. The method is applied to two human population genetic variation datasets that have been studied by sperm typing. Our results are consistent with the estimates from sperm crossover analysis.
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