Linkage disequilibrium mapping with genotype data
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Updated: Oct 3, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
1Department of Epidemiology and Public Health, Yale University School of Medicine, 60 College Street, New Haven, CT 06520-8034, USA. hongyu.zhao@yale.edu
Abstract:
Linkage disequilibrium mapping has proven a powerful tool for locating disease genes. Although all existing linkage disequilibrium mapping methods implicitly assume that individual haplotypes can be inferred, only genotypes are directly observable in practice, and haplotypes cannot always be uniquely resolved based on genotype data. In this article, we propose a likelihood-based linkage disequilibrium mapping approach to analyzing multilocus genotype data arising from case-control studies. Results from extensive simulation studies suggest that this approach may be a useful tool to fine map disease genes using case-control data.
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