Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan / Hassani-Pak, Keywan


CiteScore 2017: 0.77

SCImago Journal Rank (SJR) 2017: 0.336

Open Access
Online
ISSN
1613-4516
See all formats and pricing
More options …
Volume 13, Issue 4

Issues

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

Diogo Almeida
  • Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Laboratory for Genomics and Bioinformatic, Institute of Biological Sciences, Federal University of Pará, 66075110, Belém, Brazil
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Ida Skov
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jesper Lund
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Afsaneh Mohammadnejad
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Artur Silva
  • Laboratory for Genomics and Bioinformatic, Institute of Biological Sciences, Federal University of Pará, 66075110, Belém, Brazil
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Fabio Vandin
  • Departament of Information Engineering, University of Padova, Via Gradenigo 6/B, I-35131 Padova, Italy
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Qihua Tan
  • Unit of Human Genetics, Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, 5000 Odense, Denmark
  • Epidemiology, Biostatistics and Biodemography, Department of Public Health, Faculty of Health Science, University of Southern Denmark, 5000 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jan Baumbach
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Richard Röttger
  • Corresponding author
  • Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-04-20 | DOI: https://doi.org/10.1515/jib-2016-294

Summary

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

About the article

Published Online: 2017-04-20

Published in Print: 2016-10-01


Citation Information: Journal of Integrative Bioinformatics, Volume 13, Issue 4, Pages 24–32, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2016-294.

Export Citation

© 2016 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

Comments (0)

Please log in or register to comment.
Log in