Belleau Pascal, Deschênes Astrid, Tuveson David A, Krasnitz Alexander
Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring, NY, USA.
Cancer Center, Cold Spring Harbor Laboratory, Cold Spring, NY, USA.
Methods Mol Biol. 2025;2932:153-176. doi: 10.1007/978-1-0716-4566-6_8.
There has recently been increasing appreciation of ancestral effects on cancer genotypes and phenotypes. Consequently, the need has grown for ancestry annotation of cancer-derived molecular data. In response, we created a computational tool termed RAIDS (Robust Ancestry Inference using Data Synthesis). RAIDS is designed to infer genetic ancestry using as input sequence data from a variety of molecular protocols, even in the absence of matching cancer-free genotypes of the patient. Implemented as an R language package, RAIDS is available from the Bioconductor repository. Here we describe functionalities of RAIDS, provide instructions for its installation, give examples of its usage, and explain the interpretation of its output. While RAIDS is being actively developed, the guidance provided here is expected to apply to future refined and expanded versions of this software tool.
最近,人们越来越认识到祖先因素对癌症基因型和表型的影响。因此,对癌症衍生分子数据进行祖先注释的需求也日益增长。作为回应,我们创建了一种名为RAIDS(使用数据合成进行稳健祖先推断)的计算工具。RAIDS旨在使用来自各种分子协议的序列数据作为输入来推断遗传祖先,即使在没有患者匹配的无癌基因型的情况下也能如此。RAIDS作为一个R语言包实现,可从Bioconductor仓库获取。在这里,我们描述了RAIDS的功能,提供了其安装说明,给出了其使用示例,并解释了其输出结果的解读。虽然RAIDS正在积极开发中,但预计这里提供 的指导将适用于该软件工具未来经过改进和扩展的版本。