Work

GEInfo: an R package for gene–environment interaction analysis incorporating prior information

Year: 2022

Type: article

Abstract: SUMMARY: Gene-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 IMPLEMENTATION: The package is available at https://CRAN.R-project.org/package=GEInfo. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btac301

Authors: Xiaoyan Wang, Hongduo Liu, Shuangge Ma

Institutions: Hunan University, Yale University

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute

Awards: Novel Methods for Identifying Genetic Interactions for Cancer Prognosis, G9000144101, G9000169908, G9000286398