Genomic summary statistics and meta-analysis for set-based gene-environment interaction tests in large-scale sequencing studies
Genomic summary statistics and meta-analysis for set-based gene-environment interaction tests in large-scale sequencing studies
Abstract We propose an efficient method to generate the summary statistics for set-based gene-environment interaction tests, as well as a meta-analysis approach that aggregates the summary statistics across different studies, which can be applied to large biobank-scale sequencing studies with related samples. Simulations showed that meta-analysis is numerically concordant with the equivalent pooled analysis using individual-level data. Moreover, meta-analysis accommodates heterogeneity between studies and enhances power in multi-ethnic studies. We applied the meta-analysis approach to the whole-exome sequencing data from the UK Biobank and successfully identified gene regions associated with waist-hip ratio, as well as those with sex-specific genetic effects.
Chen Han、Pan Cong、Manning Alisa K.、Wang Xinyu、Pham Duy T.、Westerman Kenneth E.
Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston||Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at HoustonHuman Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonClinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital||Metabolism Program, Broad Institute of MIT and Harvard||Department of Medicine, Harvard Medical SchoolDepartment of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at HoustonHuman Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonClinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital||Metabolism Program, Broad Institute of MIT and Harvard||Department of Medicine, Harvard Medical School
医学研究方法基础医学遗传学
Meta-analysisgenomic summary statisticsgene-environment interactionjoint testrare variantsset-based testUK Biobank
Chen Han,Pan Cong,Manning Alisa K.,Wang Xinyu,Pham Duy T.,Westerman Kenneth E..Genomic summary statistics and meta-analysis for set-based gene-environment interaction tests in large-scale sequencing studies[EB/OL].(2025-03-28)[2025-06-06].https://www.medrxiv.org/content/10.1101/2022.05.08.22274819.点此复制
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