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Originally published as Genetics Published Articles Ahead of Print on March 1, 2006.

Genetics, Vol. 173, 1125-1133, June 2006, Copyright © 2006
doi:10.1534/genetics.105.052720

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Association Mapping With Single-Feature Polymorphisms

Sung Kim*,1, Keyan Zhao*,1, Rong Jiang*, John Molitor{dagger}, Justin O. Borevitz{ddagger}, Magnus Nordborg* and Paul Marjoram{dagger},2

* Department of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089-2910, {dagger} Department of Preventive Medicine, University of Southern California, Los Angeles, California 90089-9011 and {ddagger} Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637

2 Corresponding author: Department of Preventive Medicine, University of Southern California, 1540 Alcazar St, CHP-220, Los Angeles, CA, 90089-9011.
E-mail: pmarjora{at}usc.edu

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.




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