ArticleAmerican journal of human genetics2012
A general framework for two-stage analysis of genome-wide association studies and its application to case-control studies.
Article in American journal of human genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Two-step hypothesis testing to detect gene-environment interactions in a genome-wide scan with a survival endpoint.Statistics in medicine · 2022Article
- Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials.Biometrics · 2022Article
- Variants in PRKCE and KLC1, Potential Regulators of Type I Psoriasis.Clinical, cosmetic and investigational dermatology · 2022Article
- MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies.PLoS genetics · 2021Article
- Large-scale association analyses identify host factors influencing human gut microbiome composition.Nature genetics · 2021Article
- Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Combining controls can improve power in two-stage association studies.BMC genetics · 2018Article
- Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure.Genetic epidemiology · 2017Article
- Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification.American journal of epidemiology · 2016Article
- Gene-environment dependence creates spurious gene-environment interaction.American journal of human genetics · 2014Article
- Complex pedigrees in the sequencing era: to track transmissions or decorrelate?Genetic epidemiology · 2014Article
- Two-stage family-based designs for sequencing studies.BMC proceedings · 2014Article
- Comparisons of power of statistical methods for gene-environment interaction analyses.European journal of epidemiology · 2013Article
- Common genetic risk factors for venous thrombosis in the Chinese population.American journal of human genetics · 2013Article
- Some surprising twists on the road to discovering the contribution of rare variants to complex diseases.Human heredity · 2012Article
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Authors and funding
2 authors.
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Abstract
Two-stage analyses of genome-wide association studies have been proposed as a means to improving power for designs including family-based association and gene-environment interaction testing. In these analyses, all markers are first screened via a statistic that may not be robust to an underlying assumption, and the markers thus selected are then analyzed in a second stage with a test that is independent from the first stage and is robust to the assumption in question. We give a general formulation of two-stage designs and show how one can use this formulation both to derive existing methods and to improve upon them, opening up a range of possible further applications. We show how using simple regression models in conjunction with external data such as average trait values can improve the power of genome-wide association studies. We focus on case-control studies and show how it is possible to use allele frequencies derived from an external reference to derive a powerful two-stage analysis. An illustration involving the Wellcome Trust Case-Control Consortium data shows several genome-wide-significant associations, subsequently validated, that were not significant in the standard analysis. We give some analytic properties of the methods and discuss some underlying principles.
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