RaMWAS: fast methylome-wide association study pipeline for enrichment platforms
RaMWAS: fast methylome-wide association study pipeline for enrichment platforms
复制标题
DOI：
10.1093/bioinformatics/bty069
复制
发表时间：
2018-07-01
期刊：
影响因子：
5.8
通讯作者：
van den Oord, Edwin J. C. G.
中科院分区：
文献类型：
--
作者：
Shabalin, Andrey A.;Hattab, Mohammad W.;van den Oord, Edwin J. C. G.
动机：基于富集的技术可以为数千个样本提供数千万个CpG的DNA甲基化测量。现有的工具，甲基化全关联研究不能分析数据集的这种规模，缺乏重要的功能，如主成分分析，结合分析与SNP数据和结果的预测，是基于所有信息的methylation sites. Results：我们提出了一个Bioconductor R包称为RaMWAS与一套完整的工具，大规模的甲基化全关联研究。它是免费的，跨平台的，开源的，内存效率高，速度快。可用性和实施：发布版本和小插图与小案例研究在bioconductor。org/packages/ramwas github上的开发版本。联系人：anju.shabalin@www.example.com或ejvandenoord@vcu. edu补充信息：补充数据可在生物信息学在线获得。
Motivation: 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.Results: We present a Bioconductor R package called RaMWAS with a full set of tools for largescale methylome-wide association studies. It is free, cross-platform, open source, memory efficient and fast.Availability and implementation: Release version and vignettes with small case study at bioconductor. org/packages/ramwas Development version at github. com/andreyshabalin/ramwas.Contact: andrey.shabalin@utah.edu or ejvandenoord@vcu.eduSupplementary information: Supplementary data are available at Bioinformatics online.