Estimation of Population Parameters and Recombination Rates From Single Nucleotide Polymorphisms

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Estimation of population parameters and recombination rates from single nucleotide polymorphisms.

Some general likelihood and Bayesian methods for analyzing single nucleotide polymorphisms (SNPs) are presented. First, an efficient method for estimating demographic parameters from SNPs in linkage equilibrium is derived. The method is applied in the estimation of growth rates of a human population based on 37 SNP loci. It is demonstrated how ascertainment biases, due to biased sampling of loc...

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Maximum likelihood estimation of recombination rates from population data.

We describe a method for co-estimating r = C/mu (where C is the per-site recombination rate and mu is the per-site neutral mutation rate) and Theta = 4N(e)mu (where N(e) is the effective population size) from a population sample of molecular data. The technique is Metropolis-Hastings sampling: we explore a large number of possible reconstructions of the recombinant genealogy, weighting accordin...

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RECENT studies employing single-sperm haplotyping ( Jeffreys and Neumann 2002), pedigrees (Visser et al. 2005), and population studies using dense genetic marker data (Crawford et al. 2004; McVean et al. 2004; Myers et al. 2005) have shown that there is a large amount of local variation in recombination rate in the human genome. Methods to estimate fine-scale recombination rates from population...

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Single nucleotide polymorphisms and recombination rate in humans.

Levels of heterozygosity for single nucleotide polymorphisms vary by more than one order of magnitude in different regions of the human genome. Regional differences in the rate of recombination explain a substantial fraction of the variation in levels of nucleotide polymorphism, consistent with the widespread action of natural selection at the molecular level.

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Single Nucleotide Polymorphisms and Association Studies: A Few Critical Points

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ژورنال

عنوان ژورنال: Genetics

سال: 2000

ISSN: 1943-2631

DOI: 10.1093/genetics/154.2.931