GEInfo: an R package for gene-environment interaction analysis incorporating prior information.
GEInfo: an R package for gene-environment interaction analysis incorporating prior information.
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GEInfo：一个 R 包，用于结合先验信息进行基因-环境相互作用分析。
DOI：
10.1093/bioinformatics/btac301
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Ma,Shuangge
中科院分区：
文献类型：
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作者：
Wang,Xiaoyan;Liu,Hongduo;Ma,Shuangge
基因-环境（G-E）相互作用对许多复杂疾病有重要意义。由于G-E交互作用的维度较高，信号较弱，因此，G-E交互作用分析比主要的G（和E）效应分析更具挑战性。通过积累已发表的文献，可以从先前的信息中汲取力量，改进分析。在最近的一项研究中，开发了一种“准似然+惩罚”方法，以有效地结合先验信息。在这里，我们首先将其扩展到线性，logistic和Poisson回归。这种模式在实践中更受欢迎。更重要的是，我们开发了R包GEInfo，它以用户友好的方式实现了这种方法。为了便于直接比较和常规数据分析，该软件包还包括替代方法和可视化功能。可用性和实施该软件包可在https://CRAN.R-project.org/package=GEInfo.Supplementary信息补充材料可在Bioinformatics在线。
SummaryGene–environment (G–E) interactions have important implications for many complex diseases. With higher dimensionality and weaker signals, G–E interaction analysis is more challenged than the analysis of main G (and E) effects. The accumulation of published literature makes it possible to borrow strength from prior information and improve analysis. In a recent study, a ‘quasi-likelihood + penalization’ approach was developed to effectively incorporate prior information. Here, we first extend it to linear, logistic and Poisson regressions. Such models are much more popular in practice. More importantly, we develop the R package GEInfo, which realizes this approach in a user-friendly manner. To facilitate direct comparison and routine data analysis, the package also includes functions for alternative methods and visualization.Availability and implementationThe package is available at https://CRAN.R-project.org/package=GEInfo.Supplementary informationSupplementary materials are available atBioinformaticsonline.