Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, USA.
Department of Psychiatry, University of Utah, Salt Lake City, USA.
Bioinformatics. 2018 Jul 1;34(13):2283-2285. doi: 10.1093/bioinformatics/bty069.
Enrichment-based technologies can provide measurements of DNA methylation at tens of millions of CpGs for thousands of samples. Existing tools for methylome-wide association studies cannot analyze datasets of this size and lack important features like principal component analysis, combined analysis with SNP data and outcome predictions that are based on all informative methylation sites.
We present a Bioconductor R package called RaMWAS with a full set of tools for large-scale methylome-wide association studies. It is free, cross-platform, open source, memory efficient and fast.
Release version and vignettes with small case study at bioconductor.org/packages/ramwas Development version at github.com/andreyshabalin/ramwas.
Supplementary data are available at Bioinformatics online.
基于富集的技术可以为数千个样本的数百万个 CpG 提供 DNA 甲基化的测量。现有的全基因组甲基化关联研究工具无法分析这种规模的数据集，并且缺乏一些重要的功能，如主成分分析、与 SNP 数据的联合分析以及基于所有信息性甲基化位点的结果预测。
我们提出了一个名为 RaMWAS 的 Bioconductor R 包，它具有用于大规模全基因组甲基化关联研究的全套工具。它是免费的、跨平台的、开源的、内存高效的且快速的。
在 bioconductor.org/packages/ramwas 上提供发布版本和带有小型案例研究的说明，在 github.com/andreyshabalin/ramwas 上提供开发版本。
补充数据可在 Bioinformatics 在线获得。
