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相关论文: Significance and Stability Analysis of Gene-Enviro…

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Currently, two main approaches exist to distinguish differential susceptibility from diathesis-stress and vantage sensitivity in genotype x environment interaction (GxE) research: Regions of significance (RoS) and competitive-confirmatory…

We describe a regularized regression model for the selection of gene-environment (GxE) interactions. The model focuses on a single environmental exposure and induces a main-effect-before-interaction hierarchical structure. We propose an…

统计方法学 · 统计学 2022-02-08 Natalia Zemlianskaia , W. James Gauderman , Juan Pablo Lewinger

Gene-environment interactions have important implications to elucidate the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G$\times$E interactions…

应用统计 · 统计学 2020-03-09 Fei Zhou , Jie Ren , Xi Lu , Shuangge Ma , Cen Wu

This study introduces a framework for constructing enviromics matrices in mixed models to integrate genetic and environmental data to enhance phenotypic predictions in plant breeding. Enviromics utilizes diverse data sources, such as…

定量方法 · 定量生物学 2026-02-05 B. A. Trevisan , V. S. Junqueira , B. M. Florencio , A. S. G. Coelho , G. E. Marcatti , R. T. Resende

Motivated by the goal of expanding currently existing genotype x environment interaction (GxE) models to simultaneously include multiple genetic variants and environmental exposures in a parsimonious way, we developed a novel method to…

Economists and social scientists have debated the relative importance of nature (one's genes) and nurture (one's environment) for decades, if not centuries. This debate can now be informed by the ready availability of genetic data in a…

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…

应用统计 · 统计学 2013-05-27 Jaeil Ahn , Bhramar Mukherjee , Stephen B. Gruber , Malay Ghosh

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…

统计方法学 · 统计学 2018-10-19 Mengyun Wu , Qingzhao Zhang , Shuangge Ma

Measuring gene expression simultaneously in both hosts and symbionts offers a powerful approach to explore the biology underlying species interactions. Such dual or simultaneous RNAseq approaches have primarily been used to gain insight…

种群与进化 · 定量生物学 2022-06-28 Amanda K Hund , Peter Tiffin , Jean-Gabriel Young , Daniel I Bolnick

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…

统计方法学 · 统计学 2020-03-06 Qingzhao Zhang , Hao Chai , Shuangge Ma

It is increasingly of interest in statistical genetics to test for the presence of a mechanistic interaction between genetic (G) and environmental (E) risk factors by testing for the presence of an additive GxE interaction. In case-control…

统计方法学 · 统计学 2018-08-21 Eric J. Tchetgen Tchetgen , Xu Shi , Tamar Sofer , Benedict H. W. Wong

Variations in complex traits are influenced by multiple genetic variants, environmental risk factors, and their interactions. Though substantial progress has been made in identifying single genetic variants associated with complex traits,…

基因组学 · 定量生物学 2025-08-22 Ming Li , Ruo-Sin Peng , Changshuai Wei , Qing Lu

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…

统计方法学 · 统计学 2019-10-01 Jie Ren , Fei Zhou , Xiaoxi Li , Qi Chen , Hongmei Zhang , Shuangge Ma , Yu Jiang , Cen Wu

Cognizance of gene-environment interactions may help prevent or detain the onset of complex diseases like cardiovascular disease, cancer, type2 diabetes, autism or asthma by adjustments to lifestyle. In this regard, we extend the Bayesian…

应用统计 · 统计学 2017-07-25 Durba Bhattacharya , Sourabh Bhattacharya

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…

统计方法学 · 统计学 2016-05-31 Yangguang Zang , Yinjun Zhao , Qingzhao Zhang , Hao Chai , Sanguo Zhang , Shuangge Ma

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…

其他定量生物学 · 定量生物学 2025-07-17 Dilnoza Muslimova , Niels Rietveld

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…

应用统计 · 统计学 2014-06-19 Flora Alarcon , Vittorio Perduca , Gregory Nuel

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and…

应用统计 · 统计学 2013-05-03 Daniel E Runcie , Sayan Mukherjee

In plant breeding the presence of a genotype by environment (GxE) interaction has a strong impact on cultivation decision making and the introduction of new crop cultivars. The combination of linear and bilinear terms has been shown to be…

机器学习 · 统计学 2022-07-04 AntÔnia A. L. Dos Santos , Rafael A. Moral , Danilo A. Sarti , Andrew C. Parnell

Increasing evidence has shown that gene-gene interactions have important effects on biological processes of human diseases. Due to the high dimensionality of genetic measurements, existing interaction analysis methods usually suffer from a…

统计方法学 · 统计学 2021-01-11 Xing Qin , Shuangge Ma , Mengyun Wu
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