Simple models of genomic variation in human SNP density.

Abstract:

BACKGROUND:Descriptive hierarchical Poisson models and population-genetic coalescent mixture models are used to describe the observed variation in single-nucleotide polymorphism (SNP) density from samples of size two across the human genome. RESULTS:Using empirical estimates of recombination rate across the human genome and the observed SNP density distribution, we produce a maximum likelihood estimate of the genomic heterogeneity in the scaled mutation rate theta. Such models produce significantly better fits to the observed SNP density distribution than those that ignore the empirically observed recombinational heterogeneities. CONCLUSION:Accounting for mutational and recombinational heterogeneities can allow for empirically sound null distributions in genome scans for "outliers", when the alternative hypotheses include fundamentally historical and unobserved phenomena.

journal_name

BMC Genomics

journal_title

BMC genomics

authors

Sainudiin R,Clark AG,Durrett RT

doi

10.1186/1471-2164-8-146

subject

Has Abstract

pub_date

2007-06-06 00:00:00

pages

146

issn

1471-2164

pii

1471-2164-8-146

journal_volume

8

pub_type

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