ArticleGenetic epidemiology2013
A general framework for association tests with multivariate traits in large-scale genomics studies.
Article in Genetic epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 46 citations in OpenAlex.
- Bivariate genome-wide association study of circulating fibrinogen and C-reactive protein levels.Journal of thrombosis and haemostasis : JTH · 2024Article
- An adaptive and robust method for multi-trait analysis of genome-wide association studies using summary statistics.European journal of human genetics : EJHG · 2024Article
- Statistical Inference for High-Dimensional Pathway Analysis with Multiple Responses.Computational statistics & data analysis · 2022Article
- Disease-Associated Risk Variants inCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021Article
- Association of Melanoma-Risk Variants with Primary Melanoma Tumor Prognostic Characteristics and Melanoma-Specific Survival in the GEM Study.Current oncology (Toronto, Ont.) · 2021Article
- Comparison of adaptive multiple phenotype association tests using summary statistics in genome-wide association studies.Human molecular genetics · 2021Article
- Article
- Multi-trait analysis of rare-variant association summary statistics using MTAR.Nature communications · 2020Article
- Genome-Wide Gene-Based Multi-Trait Analysis.Frontiers in genetics · 2020Article
- Pleiotropy informed adaptive association test of multiple traits using genome-wide association study summary data.Biometrics · 2019Article
- Powerful and efficient SNP-set association tests across multiple phenotypes using GWAS summary data.Bioinformatics (Oxford, England) · 2019Article
- A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies.Journal of the American Statistical Association · 2019Article
- Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence.The annals of applied statistics · 2018Article
- Inherited Genetic Variants Associated with Melanoma BRAF/NRAS Subtypes.The Journal of investigative dermatology · 2018Article
- Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.PLoS genetics · 2018Article
- Pleiotropic mapping and annotation selection in genome-wide association studies with penalized Gaussian mixture models.Bioinformatics (Oxford, England) · 2018Article
- Multivariate association analysis with somatic mutation data.Biometrics · 2018Article
- The interaction between vitamin D receptor polymorphisms and sun exposure around time of diagnosis influences melanoma survival.Pigment cell & melanoma research · 2018Article
- Fast and Accurate Genome-Wide Association Test of Multiple Quantitative Traits.Computational and mathematical methods in medicine · 2018Article
- A functional U-statistic method for association analysis of sequencing data.Genetic epidemiology · 2017Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Genetic association studies often collect data on multiple traits that are correlated. Discovery of genetic variants influencing multiple traits can lead to better understanding of the etiology of complex human diseases. Conventional univariate association tests may miss variants that have weak or moderate effects on individual traits. We propose several multivariate test statistics to complement univariate tests. Our framework covers both studies of unrelated individuals and family studies and allows any type/mixture of traits. We relate the marginal distributions of multivariate traits to genetic variants and covariates through generalized linear models without modeling the dependence among the traits or family members. We construct score-type statistics, which are computationally fast and numerically stable even in the presence of covariates and which can be combined efficiently across studies with different designs and arbitrary patterns of missing data. We compare the power of the test statistics both theoretically and empirically. We provide a strategy to determine genome-wide significance that properly accounts for the linkage disequilibrium (LD) of genetic variants. The application of the new methods to the meta-analysis of five major cardiovascular cohort studies identifies a new locus (HSCB) that is pleiotropic for the four traits analyzed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.