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Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Study of gene-environment (G$\times$E) interactions is important for…

Methodology · Statistics 2019-10-01 Jie Ren , Fei Zhou , Xiaoxi Li , Qi Chen , Hongmei Zhang , Shuangge Ma , Yu Jiang , Cen Wu

For the etiology, progression, and treatment of complex diseases, gene-environment (G-E) interactions have important implications beyond the main G and E effects. G-E interaction analysis can be more challenging with the higher…

Methodology · Statistics 2018-10-19 Mengyun Wu , Qingzhao Zhang , Shuangge Ma

In high-throughput genetics studies, an important aim is to identify gene-environment interactions associated with the clinical outcomes. Recently, multiple marginal penalization methods have been developed and shown to be effective in…

Methodology · Statistics 2021-02-24 Xi Lu , Kun Fan , Jie Ren , Cen Wu

Gene-environment (G$\times$E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G$\times$E…

Methodology · Statistics 2020-06-11 Jie Ren , Fei Zhou , Xiaoxi Li , Shuangge Ma , Yu Jiang , Cen Wu

For complex diseases, the interactions between genetic and environmental risk factors can have important implications beyond the main effects. Many of the existing interaction analyses conduct marginal analysis and cannot accommodate the…

Methodology · Statistics 2016-05-31 Yangguang Zang , Yinjun Zhao , Qingzhao Zhang , Hao Chai , Sanguo Zhang , Shuangge Ma

The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for collecting genetic data in a subsample enriched for exposure…

Applications · Statistics 2013-05-27 Jaeil Ahn , Bhramar Mukherjee , Stephen B. Gruber , Malay Ghosh

Genome-wide association studies, in which as many as a million single nucleotide polymorphisms (SNP) are measured on several thousand samples, are quickly becoming a common type of study for identifying genetic factors associated with many…

Methodology · Statistics 2010-10-25 Charles Kooperberg , Michael LeBlanc , James Y. Dai , Indika Rajapakse

Penalized variable selection for high dimensional longitudinal data has received much attention as accounting for the correlation among repeated measurements and providing additional and essential information for improved identification and…

Methodology · Statistics 2021-07-20 Fei Zhou , Xi Lu , Jie Ren , Kun Fan , Shuangge Ma , Cen Wu

Epidemiological evidence suggests that simultaneous exposures to multiple environmental risk factors (Es) can increase disease risk larger than the additive effect of individual exposure acting alone. The interaction between a gene and…

Methodology · Statistics 2022-09-02 Shunjie Guan , Mingtao Zhao , Yuehua Cui

Interactions between genes and environmental factors may play a key role in the etiology of many common disorders. Several regularized generalized linear models (GLMs) have been proposed for hierarchical selection of gene by environment…

Methodology · Statistics 2023-12-22 Julien St-Pierre , Karim Oualkacha , Julien St-Pierre

For complex diseases, beyond the main effects of genetic (G) and environmental (E) factors, gene-environment (G-E) interactions also play an important role. Many of the existing G-E interaction methods conduct marginal analysis, which may…

Methodology · Statistics 2020-03-06 Qingzhao Zhang , Hao Chai , Shuangge Ma

Genetic variants identified to date by genome-wide association studies only explain a small fraction of total heritability. Gene-by-gene interaction is one important potential source of unexplained heritability. In the first part of this…

Methodology · Statistics 2016-05-10 Chen Lu

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the most part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.).…

Quantitative Methods · Quantitative Biology 2009-05-08 Roberto Amato , Michele Pinelli , Daniel D'Andrea , Gennaro Miele , Mario Nicodemi , Giancarlo Raiconi , Sergio Cocozza

Antagonistic interactions in biological systems, which occur when one perturbation blunts the effect of another, are typically interpreted as evidence that the two perturbations impact the same cellular pathway or function. Yet, this…

Biological Physics · Physics 2020-11-12 Thomas P. Wytock , Manjing Zhan , Adrian Jinich , Aretha Fiebig , Sean Crosson , Adilson E. Motter

For the outcomes and phenotypes of complex diseases, multiple types of molecular (genetic, genomic, epigenetic, etc.) changes, environmental risk factors, and their interactions have been found to have important contributions. In each of…

Methodology · Statistics 2019-12-19 Yaqing Xu , Mengyun Wu , Shuangge Ma

Recently more and more evidence suggests that rare variants with much lower minor allele frequencies play significant roles in disease etiology. Advances in next-generation sequencing technologies will lead to many more rare variants…

Methodology · Statistics 2014-03-05 Ruixue Fan , Shaw-Hwa Lo

This perspective posits that gene-environment interplay (GxE) studies should be developed both theoretically and empirically to be of relevance to policy makers. On the theoretical front, this development is essential because the current…

Other Quantitative Biology · Quantitative Biology 2025-07-17 Dilnoza Muslimova , Niels Rietveld

Genotype-by-Environment (GxE) interactions influence the performance of genotypes across diverse environments, reducing the predictability of phenotypes in target environments. In-depth analysis of GxE interactions facilitates the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Meng'en Qin , Zhe Li , Xiaohui Yang

Gene-gene and gene-environment interactions are widely believed to play significant roles in explaining the variability of complex traits. While substantial research exists in this area, a comprehensive statistical framework that addresses…

Methodology · Statistics 2026-02-18 Durba Bhattacharya , Sourabh Bhattacharya

It is generally acknowledged that most complex diseases are affected in part by interactions between genes and genes and/or between genes and environmental factors. Taking into account environmental exposures and their interactions with…

Applications · Statistics 2014-06-19 Flora Alarcon , Vittorio Perduca , Gregory Nuel
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