Bocher Ozvan, Marenne Gaëlle, Génin Emmanuelle, Perdry Hervé
Univ Brest, Inserm, EFS, UMR 1078, GGB, Brest, France.
Institute of Translational Genomics, Helmholtz Zentrum München, Munich, Germany.
Genet Epidemiol. 2023 Sep;47(6):450-460. doi: 10.1002/gepi.22529. Epub 2023 May 9.
Current software packages for the analysis and the simulations of rare variants are only available for binary and continuous traits. Ravages provides solutions in a single R package to perform rare variant association tests for multicategory, binary and continuous phenotypes, to simulate datasets under different scenarios and to compute statistical power. Association tests can be run in the whole genome thanks to C++ implementation of most of the functions, using either RAVA-FIRST, a recently developed strategy to filter and analyse genome-wide rare variants, or user-defined candidate regions. Ravages also includes a simulation module that generates genetic data for cases who can be stratified into several subgroups and for controls. Through comparisons with existing programmes, we show that Ravages complements existing tools and will be useful to study the genetic architecture of complex diseases. Ravages is available on the CRAN at https://cran.r-project.org/web/packages/Ravages/ and maintained on Github at https://github.com/genostats/Ravages.
当前用于分析和模拟罕见变异的软件包仅适用于二元和连续性状。Ravages在一个R包中提供了解决方案，用于对多类别、二元和连续表型进行罕见变异关联测试，在不同场景下模拟数据集并计算统计功效。由于大多数函数都用C++实现，因此可以在全基因组中运行关联测试，使用最近开发的用于筛选和分析全基因组罕见变异的RAVA-FIRST策略，或用户定义的候选区域。Ravages还包括一个模拟模块，该模块为可分为几个亚组的病例和对照生成遗传数据。通过与现有程序的比较，我们表明Ravages补充了现有工具，将有助于研究复杂疾病的遗传结构。Ravages可在CRAN上获取，网址为https://cran.r-project.org/web/packages/Ravages/，并在Github上维护，网址为https://github.com/genostats/Ravages。
