ArticleGenetic epidemiology2012
Multivariate detection of gene-gene interactions.
Article in Genetic epidemiology, 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.
- A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects.Genetic epidemiology · 2023Article
- Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search.Human heredity · 2018Article
- Eigen-Epistasis for detecting gene-gene interactions.BMC bioinformatics · 2017Article
- Influence of SNP*SNP interaction on BMI in European American adolescents: findings from the National Longitudinal Study of Adolescent Health.Pediatric obesity · 2016Article
- Article
- Statistical analysis for genome-wide association study.Journal of biomedical research · 2015Review
- Biological knowledge-driven analysis of epistasis in human GWAS with application to lipid traits.Methods in molecular biology (Clifton, N.J.) · 2015Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
- Natural and orthogonal model for estimating gene-gene interactions applied to cutaneous melanoma.Human genetics · 2014Article
- Testing gene-gene interactions in genome wide association studies.Genetic epidemiology · 2014Article
- Kernel canonical correlation analysis for assessing gene-gene interactions and application to ovarian cancer.European journal of human genetics : EJHG · 2014Article
- A powerful latent variable method for detecting and characterizing gene-based gene-gene interaction on multiple quantitative traits.BMC genetics · 2013Article
- Article
- Gene-based testing of interactions in association studies of quantitative traits.PLoS genetics · 2013Article
- A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.PloS one · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Unraveling the nature of genetic interactions is crucial to obtaining a more complete picture of complex diseases. It is thought that gene-gene interactions play an important role in the etiology of cancer, cardiovascular, and immune-mediated disease. Interactions among genes are defined as phenotypic effects that differ from those observed for independent contributions of each gene, usually detected by univariate logistic regression methods. Using a multivariate extension of linkage disequilibrium (LD), we have developed a new method, based on distances between sample covariance matrices for groups of single nucleotide polymorphisms (SNPs), to test for interaction effects of two groups of genes associated with a disease phenotype. Since a disease-associated interacting locus will often be in LD with more than one marker in the region, a method that examines a set of markers in a region collectively can offer greater power than traditional methods. Our method effectively identifies interaction effects in simulated data, as well as in data on the genetic contributions to the risk for graft-versus-host disease following hematopoietic stem cell transplantation.
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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.