Jllumina: A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing

Diogo Marinho Almeida, Ida Uhrenfeldt Skov, Jesper Lund, Afsaneh Mohammadnejad, Artur Silva, Fabio Vandin, Qihua Tan, Jan Baumbach, Richard Röttger

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Abstract

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.

Original languageEnglish
Article number294
JournalJournal of Integrative Bioinformatics
Volume13
Issue number4
Pages (from-to)294
Number of pages9
ISSN1613-4516
DOIs
Publication statusPublished - 2016

Bibliographical note

NB: Ifølge artiklen er Ida Skov, Jesper Lund og Afsaneh Mohammadnejad interne forfattere med tilknytning til IMADA

Keywords

  • Cohort Studies
  • Computational Biology
  • DNA Methylation
  • Genome-Wide Association Study
  • Humans
  • Programming Languages

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