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 Genomicsjournal_title
BMC genomicsauthors
Sainudiin R,Clark AG,Durrett RTdoi
10.1186/1471-2164-8-146subject
Has Abstractpub_date
2007-06-06 00:00:00pages
146issn
1471-2164pii
1471-2164-8-146journal_volume
8pub_type
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