作者: P. J. Heagerty , B. S. Weir
DOI: 10.1007/978-1-4614-5245-4_12
关键词: Linkage disequilibrium 、 Biology 、 Single-nucleotide polymorphism 、 Computational biology 、 Quantitative genetics 、 Human genome 、 Regression 、 Genetic marker 、 Association mapping 、 SNP
摘要: The current availability of dense sets marker SNPs for the human genome is having a large impact on genetic studies and offers new possibilities clinical trials. This chapter unified basis analysis response data, emphasizing central importance correlation, or linkage disequilibrium, between SNP markers genes that affect response. It convenient to phrase development association mapping in language quantitative genetics, using additive non-additive components variance. A novel feature data good estimates can be made actual inbreeding relatedness. These are more relevant than values predicted from family pedigree, all available absence data.The dimensionality datasets has required methods appropriate number statistical comparisons, computational allow high-dimensional regression. reviewed here, as use biological annotation both viewing relevance empirical associations, structure order focus those with highest expectation outcomes under study.