Simple models of genomic variation in human SNP density.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Sainudiin, R; Clark, AG; Durrett, RT

Published Date

  • June 2007

Published In

Volume / Issue

  • 8 /

Start / End Page

  • 146 -

PubMed ID

  • 17553150

Pubmed Central ID

  • PMC1919371

Electronic International Standard Serial Number (EISSN)

  • 1471-2164

International Standard Serial Number (ISSN)

  • 1471-2164

Digital Object Identifier (DOI)

  • 10.1186/1471-2164-8-146

Language

  • eng