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PMID: 16510789 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Association mapping with single-feature polymorphisms.

Genetics ·Vol. 173 ·No. 2 ·2006-06-00 ·Pages 1125-33

Kim S, Zhao K, Jiang R, Molitor J, Borevitz JO, Nordborg M, Marjoram P

Abstract

We develop methods for exploiting "single-feature polymorphism" data, generated by hybridizing genomic DNA to oligonucleotide expression arrays. Our methods enable the use of such data, which can be regarded as very high density, but imperfect, polymorphism data, for genomewide association or linkage disequilibrium mapping. We use a simulation-based power study to conclude that our methods should have good power for organisms like Arabidopsis thaliana, in which linkage disequilibrium is extensive, the reason being that the noisiness of single-feature polymorphism data is more than compensated for by their great number. Finally, we show how power depends on the accuracy with which single-feature polymorphisms are called.

MeSH Terms
Algorithms Alleles Arabidopsis/genetics Chromosome Mapping/methods,statistics & numerical data Cluster Analysis Data Interpretation, Statistical Genetic Markers Haplotypes Linkage Disequilibrium Models, Genetic Polymorphism, Genetic
Chemicals
Genetic Markers
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Kim Sung
Department of Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089-2910, USA.
Zhao Keyan
Jiang Rong
Molitor John
Borevitz Justin O
Nordborg Magnus
Marjoram Paul
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Article Info
Journal
Genetics
Abbr.
Genetics
ISSN
0016-6731
DOI
10.1534/genetics.105.052720
Published
2006-06-00
Epub
2006-00-01
Pages
1125-33
Language
English
Region
United States
NLM ID
0374636
PMCID
PMC1526505
Subset
IM
Grants
NHGRI NIH HHS · P50 HG002790 · United States
NIGMS NIH HHS · R01 GM069890 · United States
PHS HHS · FM069890-01A1 · United States
NHGRI NIH HHS · HG002790-01A1 · United States
External Links
PubMed source DOI: 10.1534/genetics.105.052720 PMC Full Text View journal details
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