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Bigmelon: tools for analysing large DNA methylation datasets

Gorrie-Stone, TJ and Smart, MC and Saffari, A and Malki, K and Hannon, E and Burrage, J and Mill, J and Kumari, M and Schalkwyk, LC (2018) 'Bigmelon: tools for analysing large DNA methylation datasets.' Bioinformatics. ISSN 1367-4803

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Abstract

MotivationThe 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.ResultsHere 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 implementationThe 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.

Item Type: Article
Additional Information: 10.1093/bioinformatics/bty713
Subjects: Q Science > QH Natural history > QH426 Genetics
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Divisions: Faculty of Science and Health > Biological Sciences, School of
Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Elements
Date Deposited: 05 Oct 2018 15:41
Last Modified: 05 Oct 2018 15:41
URI: http://repository.essex.ac.uk/id/eprint/23213

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