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Updated: May 12, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Powerful tests for association on quantitative trait loci incorporating imprinting effects
Fan Xia1, Ji-Yuan Zhou, Wing Kam Fung
1Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Hong Kong.
This study introduces novel family-based association tests, Q-C-TDTI(c) and Q-C-MAX(c), for quantitative traits, incorporating genomic imprinting without Hardy-Weinberg equilibrium assumptions. These methods offer robust performance and accommodate complex family data structures.
Area of Science:
- Epigenetics
- Statistical Genetics
- Human Genetics
Background:
- Genomic imprinting is a key epigenetic mechanism influencing complex traits.
- Existing association studies for quantitative traits incorporating imprinting often rely on Hardy-Weinberg equilibrium or limited family data.
- There is a need for flexible methods that accommodate complex family structures and diverse genotypic data.
Purpose of the Study:
- To develop novel family-based association tests for quantitative traits that incorporate genomic imprinting.
- To address limitations of existing methods by not assuming Hardy-Weinberg equilibrium and accommodating incomplete parental genotypes and multiple siblings.
- To offer robust and versatile statistical tools for genetic association studies.
Main Methods:
- Proposed two novel classes of tests: Q-C-TDTI(c) and Q-C-MAX(c).
- Q-C-TDTI(c) utilizes a two-stage approach: first, testing imprinting effects with Q-C-PAT(c), then selecting an appropriate transmission disequilibrium test statistic.
- Q-C-MAX(c) involves taking the maximum of three transmission disequilibrium test statistics.
- Methods accommodate family data with missing parental genotypes and multiple siblings, without assuming trait distribution.
Main Results:
- Simulation results demonstrate that the proposed Q-C-TDTI(c) and Q-C-MAX(c) tests are robust to population stratification.
- The new tests exhibit superior performance compared to existing methods across various scenarios.
- The Q-C-TDTI(c) test was successfully applied to analyze data from the Framingham Heart Study.
Conclusions:
- The developed Q-C-TDTI(c) and Q-C-MAX(c) tests provide powerful and versatile tools for family-based association studies of quantitative traits, particularly when considering genomic imprinting.
- These methods overcome key limitations of previous approaches, enhancing the ability to study complex traits.
- The application to the Framingham Heart Study highlights the practical utility of these novel statistical tests in real-world genetic research.
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