ArticleHuman genetics2014
A unified GMDR method for detecting gene-gene interactions in family and unrelated samples with application to nicotine dependence.
Article in Human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 22 citations in OpenAlex.
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- Correlations of SDF-1ɑ and XRCC1 gene polymorphisms with the risk of renal cancer development and bioinformatics studies of SDF-1α and XRCC1 and the prognosis of renal cancer.Scientific reports · 2024Article
- Inflammation and endothelial function relevant genetic polymorphisms, carotid atherosclerosis, and vascular events in high-risk stroke population.Frontiers in neurology · 2024Article
- GADGETS: a genetic algorithm for detecting epistasis using nuclear families.Bioinformatics (Oxford, England) · 2022Article
- Gene-gene and gene-environment interactions on cord blood total IgE in Chinese Han children.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2021Article
- Endocannabinoid Gene × Gene Interaction Association to Alcohol Use Disorder in Two Adolescent Cohorts.Frontiers in psychiatry · 2021Article
- Subcutaneous fat mass is associated with genetic risk scores related to proinflammatory cytokine signaling and interact with physical activity in middle-aged obese adults.Nutrition & metabolism · 2019Article
- An empirical fuzzy multifactor dimensionality reduction method for detecting gene-gene interactions.BMC genomics · 2017Article
- GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits.Current genomics · 2016Article
- A roadmap to multifactor dimensionality reduction methods.Briefings in bioinformatics · 2016Review
- UGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits.Heredity · 2015Article
- Article
- Gene-Gene and Gene-Environment Interactions Underlying Complex Traits and their Detection.Biometrics & biostatistics international journalArticle
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Gene-gene and gene-environment interactions govern a substantial portion of the variation in complex traits and diseases. In convention, a set of either unrelated or family samples are used in detection of such interactions; even when both kinds of data are available, the unrelated and the family samples are analyzed separately, potentially leading to loss in statistical power. In this report, to detect gene-gene interactions we propose a generalized multifactor dimensionality reduction method that unifies analyses of nuclear families and unrelated subjects within the same statistical framework. We used principal components as genetic background controls against population stratification, and when sibling data are included, within-family control were used to correct for potential spurious association at the tested loci. Through comprehensive simulations, we demonstrate that the proposed method can remarkably increase power by pooling unrelated and offspring's samples together as compared with individual analysis strategies and the Fisher's combining p value method while it retains a controlled type I error rate in the presence of population structure. In application to a real dataset, we detected one significant tetragenic interaction among CHRNA4, CHRNB2, BDNF, and NTRK2 associated with nicotine dependence in the Study of Addiction: Genetics and Environment sample, suggesting the biological role of these genes in nicotine dependence development.
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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.