Inference of the Haplotype Effect in a Matched Case-Control Study Using Unphased Genotype Data

Sinha Samiran, Gruber Stephen B, Mukherjee Bhramar and Rennert Gad
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Sinha Samiran: Texas A&M University
Gruber Stephen B: University of Michigan
Mukherjee Bhramar: University of Michigan
Rennert Gad: Carmel Medical Center; Technion-Israel Institute of Technology; CHS National Cancer Control Center

The International Journal of Biostatistics, 2008, vol. 4, issue 1, 28

Abstract: Typically locus specific genotype data do not contain information regarding the gametic phase of haplotypes, especially when an individual is heterozygous at more than one locus among a large number of linked polymorphic loci. Thus, studying disease-haplotype association using unphased genotype data is essentially a problem of handling a missing covariate in a case-control design. There are several methods for estimating a disease-haplotype association parameter in a matched case-control study. Here we propose a conditional likelihood approach for inference regarding the disease-haplotype association using unphased genotype data arising from a matched case-control study design. The proposed method relies on a logistic disease risk model and a Hardy-Weinberg equilibrium (HWE) among the control population only. We develop an expectation and conditional maximization (ECM) algorithm for jointly estimating the haplotype frequency and the disease-haplotype association parameter(s). We apply the proposed method to analyze the data from the Alpha-Tocopherol, Beta-Carotene Cancer prevention study, and a matched case-control study of breast cancer patients conducted in Israel. The performance of the proposed method is evaluated via simulation studies.

Keywords: conditional logistic regression; ECM algorithm; haplotype; matched case-control study; unphased genotype data (search for similar items in EconPapers)
Date: 2008
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DOI: 10.2202/1557-4679.1079

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