ArticleGenome research2014
Epistasis analysis for quantitative traits by functional regression model.
Article in Genome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.European journal of human genetics : EJHG · 2017Pooled it
- Meta-analysis of Complex Diseases at Gene Level with Generalized Functional Linear Models.Genetics · 2016Pooled it
- Evaluation of epistasis detection methods for quantitative phenotypes.Bioinformatics (Oxford, England) · 2026Article
- Polygenic risk for schizophrenia is associated with white matter microstructure, cognitive and mental health.Schizophrenia (Heidelberg, Germany) · 2025Article
- iRUNNER: A Baseline Mutation Burden Regression for Identifying Gene Interaction Between Rare Variants for Diseases.Genomics, proteomics & bioinformatics · 2025Article
- A Natural Major Module Confers the Trade-Off between Phenotypic Mean and Plasticity of Grain Chalkiness in Rice.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Genome-wide association mapping and transcriptional analysis uncover genetic determinants of minor tocopherols in rice seeds.Scientific reports · 2025Article
- GRAMMAR-Lambda Delivers Efficient Understanding of the Genetic Basis for Head Size in Catfish.Biology · 2025Article
- Genome-wide association study and genotypic variation for the major tocopherol content in rice grain.Frontiers in plant science · 2024Article
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- Compressed variance component mixed model reveals epistasis associated with flowering inFrontiers in plant science · 2023Article
- Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration.Journal of the American Statistical Association · 2021Article
- Human L1 Transposition Dynamics Unraveled with Functional Data Analysis.Molecular biology and evolution · 2020Article
- Genetic control of non-genetic inheritance in mammals: state-of-the-art and perspectives.Mammalian genome : official journal of the International Mammalian Genome Society · 2020Review
- How to increase our belief in discovered statistical interactions via large-scale association studies?Human genetics · 2019Review
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- Behçet's disease and genetic interactions between HLA-B*51 and variants in genes of autoinflammatory syndromes.Scientific reports · 2019Article
- A rapid epistatic mixed-model association analysis by linear retransformations of genomic estimated values.Bioinformatics (Oxford, England) · 2018Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study.
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Registered trials
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.