Gene-Based Methods to Detect Gene-Gene Interaction in R: The GeneGeneInteR Package
Gene-Based Methods to Detect Gene-Gene Interaction in R: The GeneGeneInteR Package
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DOI：
10.18637/jss.v095.i12
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发表时间：
2020-10-01
影响因子：
5.8
通讯作者：
Houee-Bigot, Magalie
中科院分区：
文献类型：
--
作者：
Emily, Mathieu;Sounac, Nicolas;Houee-Bigot, Magalie
GeneGeneInteR是一个R软件包，专门用于在病例对照全基因组关联研究中检测病例对照表型与两组双等位基因标记（单核苷酸多态性或SNP）之间的相互作用之间的关联。在SNP集水平上搜索基因-基因相互作用的统计程序的发展最近确实越来越受欢迎，因为这些方法在统计能力和生物学解释方面都具有优势。然而，所有这些方法都是在自制软件中实现的，这些软件中的大多数只能根据作者的要求提供，最多只有一个Web界面。由于这些方法的实现并不简单，因此需要一种用户友好的工具来执行基于基因的基因相互作用。GeneGeneInteR的目的是为病例对照关联研究中基于基因的基因-基因相互作用测试的所有步骤提供一系列工具。以类风湿性关节炎相关数据集为例，本文详细介绍了GeneGeneInteR中可用的功能的实现，以执行SNP集集合的分析。这种分析的目的是处理从数据输入到通过数据处理和统计分析使结果可视化的整个统计流程。
GeneGeneInteR is an R package dedicated to the detection of an association between a case-control phenotype and the interaction between two sets of biallelic markers (single nucleotide polymorphisms or SNPs) in case-control genome-wide associations studies. The development of statistical procedures for searching gene-gene interaction at the SNP-set level has indeed recently grown in popularity as these methods confer advantage in both statistical power and biological interpretation. However, all these methods have been implemented in home made softwares that are for most of them available only on request to the authors and at best have a web interface. Since the implementation of these methods is not straightforward, there is a need for a user-friendly tool to perform gene-based genegene interaction. The purpose of GeneGeneInteR is to propose a collection of tools for all the steps involved in gene-based gene-gene interaction testing in case-control association studies. Illustrated by an example of a dataset related to rheumatoid arthritis, this paper details the implementation of the functions available in GeneGeneInteR to perform an analysis of a collection of SNP sets. Such an analysis aims at addressing the complete statistical pipeline going from data importation to the visualization of the results through data manipulation and statistical analysis.