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Updated: Jun 20, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Methods for multiancestry genome-wide association study meta-analysis
Chuan Fu Yap1, Andrew P Morris1
1Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.
Abstract:
Genome-wide association studies (GWAS) have significantly enhanced our understanding of the genetic basis of complex diseases. Despite the technological advancements, gaps in our understanding remain, partly due to small effect sizes and inadequate coverage of genetic variation. Multiancestry GWAS meta-analysis (MAGMA) addresses these challenges by integrating genetic data from diverse populations, thereby increasing power to detect loci and improving fine-mapping resolution to identify causal variants across different ancestry groups. This review provides an overview of the protocols, statistical methods, and software of MAGMA, as well as highlighting some challenges associated with this approach.
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