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

Research output: Contribution to journalJournal articleResearchpeer-review

53 Downloads (Pure)

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.
Original languageEnglish
Article number294
JournalJournal of Integrative Bioinformatics
Volume13
Issue number4
Number of pages9
ISSN1613-4516
DOIs
Publication statusPublished - 2016

Fingerprint

Statistical Data Interpretation
Libraries
DNA Methylation
Computational Biology
Epigenomics
Reading

Cite this

@article{e19bfa0a9d5a42eebf62973bfe398017,
title = "Jllumina: A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing",
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.",
author = "Almeida, {Diogo Marinho} and {Uhrenfeldt Skov}, Ida and Jesper Lund and Afsaneh Mohammadnejad and Artur Silva and Fabio Vandin and Qihua Tan and Jan Baumbach and Richard R{\"o}ttger",
note = "NB: If{\o}lge artiklen er Ida Skov, Jesper Lund og Afsaneh Mohammadnejad interne forfattere med tilknytning til IMADA",
year = "2016",
doi = "10.2390/biecoll-jib-2016-294",
language = "English",
volume = "13",
journal = "Journal of Integrative Bioinformatics",
issn = "1613-4516",
publisher = "IMBIO e.V.",
number = "4",

}

Jllumina : A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing. / Almeida, Diogo Marinho; Uhrenfeldt Skov, Ida; Lund, Jesper; Mohammadnejad, Afsaneh; Silva, Artur; Vandin, Fabio; Tan, Qihua; Baumbach, Jan; Röttger, Richard.

In: Journal of Integrative Bioinformatics, Vol. 13, No. 4, 294, 2016.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Jllumina

T2 - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing

AU - Almeida, Diogo Marinho

AU - Uhrenfeldt Skov, Ida

AU - Lund, Jesper

AU - Mohammadnejad, Afsaneh

AU - Silva, Artur

AU - Vandin, Fabio

AU - Tan, Qihua

AU - Baumbach, Jan

AU - Röttger, Richard

N1 - NB: Ifølge artiklen er Ida Skov, Jesper Lund og Afsaneh Mohammadnejad interne forfattere med tilknytning til IMADA

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

UR - http://dimmer.compbio.sdu.dk/download.html

U2 - 10.2390/biecoll-jib-2016-294

DO - 10.2390/biecoll-jib-2016-294

M3 - Journal article

VL - 13

JO - Journal of Integrative Bioinformatics

JF - Journal of Integrative Bioinformatics

SN - 1613-4516

IS - 4

M1 - 294

ER -