Selecting SNPs in two-stage analysis of disease association data: a model-free approach
Selecting SNPs in two-stage analysis of disease association data: a model-free approach
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DOI：
10.1046/j.1469-1809.2000.6450413.x
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发表时间：
2000-09-01
影响因子：
1.9
通讯作者：
Ott, J
中科院分区：
文献类型：
--
作者：
Hoh, J;Wille, A;Ott, J
For large numbers of marker loci in a genomic scan for disease loci, we propose a novel 2-stage approach for linkage or association analysis. The two stages are (1) selection of a subset of markers that are 'important' for the trait studied, and (2) modelling interactions among markers and between markers and trait. Here we focus on stage 1 and develop a select ion method based on a 2-level nested bootstrap procedure. The met hod is applied to single nucleotide polymorphisms (SNPs) data in a cohort study of heart disease patients. Out of the 89 original SNPs the method selects 11 markers as being 'important'. Conventional backward stepwise logistic regression on the 89 SNPs selects 7 markers. which are a subset of the 11 markers chosen br our method.
