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Related Experiment Video

Updated: May 21, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization

Nizar Touleimat1, Jörg Tost

  • 1Laboratory for Epigenetics, Centre National de Génotypage, CEA-Institute de Génomique, Bâtiment G2, 2 rue Gaston Crémieux, Evry, France.

Epigenomics
|June 14, 2012
PubMed
Summary

A new normalization method addresses biases in DNA methylation analysis from the Illumina 450K BeadChip. This approach improves data accuracy for large-scale epigenotyping studies.

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Area of Science:

  • Epigenetics
  • Genomics
  • Bioinformatics

Background:

  • Advancements in DNA methylation analysis technologies enable large-scale epigenotyping.
  • The Illumina 450K BeadChip monitors over 480,000 CpG sites but uses dual chemistries, potentially introducing bias.
  • Merging signals from different chemistries can compromise methylation measurement accuracy.

Purpose of the Study:

  • To address the bias caused by dual assay chemistries in Illumina 450K BeadChip data.
  • To develop a robust normalization strategy for accurate DNA methylation analysis.
  • To improve the reliability of large-scale epigenotyping studies.

Main Methods:

  • Evaluated Infinium I and II probe methylation profiles across different normalization protocols.
  • Confirmed Infinium I signals offer greater stability and dynamic range than Infinium II.
  • Compared array-based methylation values with pyrosequencing data for validation.

Main Results:

  • Developed a subset quantile normalization approach for 450K BeadChip data.
  • Utilized Infinium I signals as anchors to normalize Infinium II signals.
  • Demonstrated superior bias correction and methylation signal estimation compared to existing methods.

Conclusions:

  • A complete preprocessing pipeline for 450K BeadChip data was developed.
  • The pipeline incorporates a novel subset quantile normalization for sample normalization and Infinium I/II shift correction.
  • Freely available scripts enable researchers to focus on biological discoveries, such as DNA methylation signatures.