Bigmelon: tools for analysing large DNA methylation datasets
Bigmelon: tools for analysing large DNA methylation datasets
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DOI：
10.1093/bioinformatics/bty713
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发表时间：
2019-03-15
期刊：
影响因子：
5.8
通讯作者：
Schalkwyk, Leonard C.
中科院分区：
文献类型：
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作者：
Gorrie-Stone, Tyler J.;Smart, Melissa C.;Schalkwyk, Leonard C.
DNA甲基化分析产生的数据集越来越大。随着HumanMethylationEPIC微阵列和包含数千个样本的数据集的发布，由于大量的内存需求，使用R分析这些大型数据集变得不切实际。因此，越来越需要计算效率高的方法来执行有意义的分析高维data.Results在这里，我们介绍了bigmelon R包，它提供了一个内存高效的工作流程，使用户能够执行复杂的，大规模的分析所需的表观基因组广泛的关联研究（EWAS），而不需要大型RAM。基于CoreArray Genomic Data Structure文件格式和gdsfmt包中的库，我们提供了一个实用的工作流程，可以方便DNA甲基化数据的读入，预处理，质量控制和统计分析。我们证明了bigmelon包的能力，使用一个大的数据集，包括1193人的血液样本，从理解社会：英国家庭纵向研究，测定EPIC微阵列platform.Availability和实施的bigmelon包可在Bioconductor（http：//bioconductor.org/packages/bigmelon/）。了解社会数据集可在https://www.understandingsociety.ac.uk/about/health/data上索取。补充信息补充数据可在生物信息学在线上获得。
Motivation The datasets generated by DNA methylation analyses are getting bigger. With the release of the HumanMethylationEPIC micro-array and datasets containing thousands of samples, analyses of these large datasets using R are becoming impractical due to large memory requirements. As a result there is an increasing need for computationally efficient methodologies to perform meaningful analysis on high dimensional data.Results Here we introduce the bigmelon R package, which provides a memory efficient workflow that enables users to perform the complex, large scale analyses required in epigenome wide association studies (EWAS) without the need for large RAM. Building on top of the CoreArray Genomic Data Structure file format and libraries packaged in the gdsfmt package, we provide a practical workflow that facilitates the reading-in, preprocessing, quality control and statistical analysis of DNA methylation data. We demonstrate the capabilities of the bigmelon package using a large dataset consisting of 1193 human blood samples from the Understanding Society: UK Household Longitudinal Study, assayed on the EPIC micro-array platform.Availability and implementation The bigmelon package is available on Bioconductor (http://bioconductor.org/packages/bigmelon/). The Understanding Society dataset is available at https://www.understandingsociety.ac.uk/about/health/data upon request.Supplementary informationSupplementary data are available at Bioinformatics online.