Ravages:一个R软件包,用于模拟和分析多类别表型中的罕见变异

IF 1.7 4区 医学 Q3 GENETICS & HEREDITY Genetic Epidemiology Pub Date : 2023-05-09 DOI:10.1002/gepi.22529
Ozvan Bocher, Gaëlle Marenne, Emmanuelle Génin, Hervé Perdry
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引用次数: 0

摘要

目前用于分析和模拟稀有变异的软件包仅适用于二进制和连续特征。Ravages在单个R包中提供解决方案,用于执行多类别、二元和连续表型的罕见变异关联测试,模拟不同场景下的数据集,并计算统计功率。关联测试可以在整个基因组中运行,这要归功于c++实现的大部分功能,使用RAVA-FIRST(一种最近开发的过滤和分析全基因组罕见变异的策略)或用户定义的候选区域。Ravages还包括一个模拟模块,该模块可以生成病例的遗传数据,这些病例可以分层为几个子组和对照组。通过与现有程序的比较,我们表明Ravages补充了现有工具,并将有助于研究复杂疾病的遗传结构。Ravages可以在CRAN (https://cran.r-project.org/web/packages/Ravages/)上获得,并在Github (https://github.com/genostats/Ravages)上维护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes

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.

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来源期刊
Genetic Epidemiology
Genetic Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
4.40
自引率
9.50%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations. Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.
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