Almeida Diogo, Skov Ida, Lund Jesper, Mohammadnejad Afsaneh, Silva Artur, Vandin Fabio, Tan Qihua, Baumbach Jan, Röttger Richard
J Integr Bioinform. 2016 Dec 18;13(4):294. doi: 10.2390/biecoll-jib-2016-294.
Measuring differential methylation of the DNA is the nowadays most common approach to linking epigenetic modifications to diseases (called epigenome-wide association studies, EWAS). For its low cost, its efficiency and easy handling, the Illumina HumanMethylation450 BeadChip and its successor, the Infinium MethylationEPIC BeadChip, is the by far most popular techniques for conduction EWAS in large patient cohorts. Despite the popularity of this chip technology, raw data processing and statistical analysis of the array data remains far from trivial and still lacks dedicated software libraries enabling high quality and statistically sound downstream analyses. As of yet, only R-based solutions are freely available for low-level processing of the Illumina chip data. However, the lack of alternative libraries poses a hurdle for the development of new bioinformatic tools, in particular when it comes to web services or applications where run time and memory consumption matter, or EWAS data analysis is an integrative part of a bigger framework or data analysis pipeline. We have therefore developed and implemented Jllumina, an open-source Java library for raw data manipulation of Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data, supporting the developer with Java functions covering reading and preprocessing the raw data, down to statistical assessment, permutation tests, and identification of differentially methylated loci. Jllumina is fully parallelizable and publicly available at http://dimmer.compbio.sdu.dk/download.html.
测量DNA的差异甲基化是目前将表观遗传修饰与疾病联系起来的最常用方法(称为全表观基因组关联研究,EWAS)。由于其成本低、效率高且易于操作,Illumina HumanMethylation450 BeadChip及其后续产品Infinium MethylationEPIC BeadChip是目前在大型患者队列中进行EWAS最受欢迎的技术。尽管这种芯片技术很受欢迎,但阵列数据的原始数据处理和统计分析仍然远非易事,并且仍然缺乏能够进行高质量和统计上合理的下游分析的专用软件库。到目前为止,只有基于R的解决方案可免费用于Illumina芯片数据的低级处理。然而,缺乏替代库对新生物信息学工具的开发构成了障碍,特别是在涉及运行时间和内存消耗很重要的网络服务或应用程序时,或者EWAS数据分析是更大框架或数据分析管道的一个集成部分时。因此,我们开发并实现了Jllumina,这是一个用于Illumina Infinium HumanMethylation450和Infinium MethylationEPIC BeadChip数据原始数据处理的开源Java库,为开发人员提供了涵盖读取和预处理原始数据、直至统计评估、置换检验以及差异甲基化位点识别的Java函数。Jllumina完全可并行化,可在http://dimmer.compbio.sdu.dk/download.html上公开获取。