ArticlePloS one2014
Multivariate dimensionality reduction approaches to identify gene-gene and gene-environment interactions underlying multiple complex traits.
Article in PloS one, 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.
- Reveal genomic insights into cotton domestication and improvement using gene level functional haplotype-based GWAS.Nature communications · 2025Article
- Laser-Induced Breakdown Spectroscopy Combined with Nonlinear Manifold Learning for Improvement Aluminum Alloy Classification Accuracy.Sensors (Basel, Switzerland) · 2022Article
- Article
- Endothelin-1 rs9296344 associates with the susceptibility of childhood primary nephrotic syndrome.Journal of clinical laboratory analysis · 2020Article
- Multivariate Cluster-Based Multifactor Dimensionality Reduction to Identify Genetic Interactions for Multiple Quantitative Phenotypes.BioMed research international · 2019Article
- Observational
- Genetically-Driven Enhancement of Dopaminergic Transmission Affects Moral Acceptability in Females but Not in Males: A Pilot Study.Frontiers in behavioral neuroscience · 2017Article
- Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease.Frontiers in cardiovascular medicine · 2017Review
- GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits.Current genomics · 2016Article
- Using the Generalized Index of Dissimilarity to Detect Gene-Gene Interactions in Multi-Class Phenotypes.PloS one · 2016Article
- Article
- Novel Online Dimensionality Reduction Method with Improved Topology Representing and Radial Basis Function Networks.PloS one · 2015Article
- 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
6 authors.
Funding
Abstract
The elusive but ubiquitous multifactor interactions represent a stumbling block that urgently needs to be removed in searching for determinants involved in human complex diseases. The dimensionality reduction approaches are a promising tool for this task. Many complex diseases exhibit composite syndromes required to be measured in a cluster of clinical traits with varying correlations and/or are inherently longitudinal in nature (changing over time and measured dynamically at multiple time points). A multivariate approach for detecting interactions is thus greatly needed on the purposes of handling a multifaceted phenotype and longitudinal data, as well as improving statistical power for multiple significance testing via a two-stage testing procedure that involves a multivariate analysis for grouped phenotypes followed by univariate analysis for the phenotypes in the significant group(s). In this article, we propose a multivariate extension of generalized multifactor dimensionality reduction (GMDR) based on multivariate generalized linear, multivariate quasi-likelihood and generalized estimating equations models. Simulations and real data analysis for the cohort from the Study of Addiction: Genetics and Environment are performed to investigate the properties and performance of the proposed method, as compared with the univariate method. The results suggest that the proposed multivariate GMDR substantially boosts statistical power.
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