title: Association mapping with single-feature polymorphisms.
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.
authors.affiliation: Department of Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089-2910, USA.
authors.forename: Sung
authors.initials: S
authors.lastname: Kim
authors.forename: Keyan
authors.initials: K
authors.lastname: Zhao
authors.forename: Rong
authors.initials: R
authors.lastname: Jiang
authors.forename: John
authors.initials: J
authors.lastname: Molitor
authors.forename: Justin O
authors.initials: JO
authors.lastname: Borevitz
authors.forename: Magnus
authors.initials: M
authors.lastname: Nordborg
authors.forename: Paul
authors.initials: P
authors.lastname: Marjoram
mesh_terms: D000465:Algorithms; D000483:Alleles; D017360:Arabidopsis / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D005819:Genetic Markers; D006239:Haplotypes; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D011110:Polymorphism, Genetic
chemical_list: D005819:Genetic Markers