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PMID: 15371362 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S.

Reconstituting the frequency spectrum of ascertained single-nucleotide polymorphism data.

Genetics ·Vol. 168 ·No. 4 ·2004-12-00 ·Pages 2373-82

Nielsen R, Hubisz MJ, Clark AG

Abstract

Most of the available SNP data have eluded valid population genetic analysis because most population genetical methods do not correctly accommodate the special discovery process used to identify SNPs. Most of the available SNP data have allele frequency distributions that are biased by the ascertainment protocol. We here show how this problem can be corrected by obtaining maximum-likelihood estimates of the true allele frequency distribution. In simple cases, the ML estimate of the true allele frequency distribution can be obtained analytically, but in other cases computational methods based on numerical optimization or the EM algorithm must be used. We illustrate the new correction method by analyzing some previously published SNP data from the SNP Consortium. Appropriate treatment of SNP ascertainment is vital to our ability to make correct inferences from the data of the International HapMap Project.

MeSH Terms
Alleles Data Interpretation, Statistical Gene Frequency Genetic Variation Models, Genetic Polymorphism, Single Nucleotide
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Nielsen Rasmus
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA. [email protected] <[email protected]>
Hubisz Melissa J
Clark Andrew G
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Article Info
Journal
Genetics
Abbr.
Genetics
ISSN
0016-6731
Published
2004-12-00
Epub
2004-00-15
Pages
2373-82
Language
English
Region
United States
NLM ID
0374636
PMCID
PMC1448751
Subset
IM
Grants
NHGRI NIH HHS · R01 HG003229 · United States
PHS HHS · 0201037 · United States
NHGRI NIH HHS · HG03229 · United States
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