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Updated: Oct 27, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Systematic comparison of phenome-wide admixture mapping and genome-wide association at biobank-scale
Sinead Cullina1,2, Ruhollah Shemirani1, Zhuozheng Shi3,4
1Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Abstract:
Opportunities remain to leverage population structure in large scale genomic studies for additional insight. Admixture mapping (AM) identifies loci where disease risk differs by ancestral background, offering a complementary strategy to genome-wide association studies (GWAS) in admixed populations. We performed a systematic comparison of AM and GWAS across over 800 clinical phenotypes in Hispanic/Latino (HL) and African American (AA) participants from the BioMe biobank. We developed a well-calibrated AM pipeline tailored to the local ancestry structure of HL (N = 14,876) and AA (N = 8,819). While GWAS identified a greater number of significant associations, AM revealed 77 signals, including 48 not detected by GWAS. AM-tagged variants had higher minor allele frequency and population differentiation (Fst), while GWAS demonstrated higher odds ratios, underscoring the distinct genetic architecture identified by each method. This study emphasizes the importance of applying both GWAS and AM approaches to uncover previously unreported loci in admixed populations.
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