Selecting SNPs in Two-stage Analysis of Disease Association Data: a Model-free Approach

Overview

Journal Ann Hum Genet

Date 2001 Apr 3

PMID 11281279

Citations 30

Authors

J Hoh

A Wille

R Zee

S Cheng

R Reynolds

K Lindpaintner

J Ott

Affiliations

Soon will be listed here.

Abstract

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 selection method based on a 2-level nested bootstrap procedure. The method 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 by our method.

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