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Related Experiment Video

Updated: Mar 9, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi.

Jean-Philippe Fortin1, Timothy J Triche2, Kasper D Hansen1,3

  • 1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.

Bioinformatics (Oxford, England)
|December 31, 2016
PubMed
Summary
This summary is machine-generated.

The minfi package now supports Illumina

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Area of Science:

  • Genomics
  • Epigenetics
  • Bioinformatics

Background:

  • The minfi package is a popular tool for DNA methylation array analysis.
  • Illumina's HumanMethylationEPIC array presents new analytical challenges.
  • Integrating data across different Illumina array generations is complex.

Purpose of the Study:

  • To update the minfi package for compatibility with the HumanMethylationEPIC array.
  • To develop methods for joint analysis and normalization of 450k and EPIC data.
  • To introduce a novel normalization method for incremental preprocessing.

Main Methods:

  • Modified the minfi package to support the HumanMethylationEPIC array.
  • Developed joint analysis and normalization strategies for 450k and EPIC data.
  • Introduced the single-sample Noob (ssNoob) normalization method.

Main Results:

  • The updated minfi package seamlessly integrates HumanMethylationEPIC data.
  • The ssNoob method enables effective incremental preprocessing of methylation arrays.
  • Reference 450k datasets can be used to estimate cell type composition on EPIC arrays.

Conclusions:

  • The enhanced minfi package provides comprehensive tools for analyzing diverse Illumina methylation array data.
  • The ssNoob method is recommended for integrating data from multiple Infinium methylation array generations.
  • minfi now facilitates robust analysis and integration of current and future Illumina methylation data.