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Infinium Assay for Large-scale SNP Genotyping Applications
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A Guide to Illumina BeadChip Data Analysis.

Michael C Wu1, Pei-Fen Kuan2

  • 1Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M3-C102, Seattle, WA, 98109, USA. mcwu@fhcrc.org.

Methods in Molecular Biology (Clifton, N.J.)
|December 11, 2017
PubMed
Summary
This summary is machine-generated.

This chapter details analyzing Illumina BeadChip data for genome-wide DNA methylation profiling. It covers preprocessing, quality control, normalization, and association testing for complex disease research.

Keywords:
DNA methylationEpigenome-wide association studiesHypothesis testingNormalizationPathway analysisQuality control

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Area of Science:

  • Epigenetics and Genomics
  • Bioinformatics and Computational Biology

Background:

  • Illumina Infinium BeadChips offer genome-wide DNA methylation profiling at over 485,000 (450K) and 850,000 (EPIC) CpG sites.
  • This platform is crucial for large-scale population studies investigating complex diseases and environmental exposures.

Purpose of the Study:

  • To provide a comprehensive overview of analyzing Illumina BeadChip data.
  • To guide researchers through essential data processing and association testing methodologies.

Main Methods:

  • Data extraction and rigorous quality control procedures.
  • Normalization strategies to ensure data comparability.
  • Association analysis at both individual CpG sites and pathway levels.

Main Results:

  • Established key preprocessing steps for reliable Illumina BeadChip data analysis.
  • Presented methods for conducting robust association analyses.
  • Provided guidelines for interpreting results from DNA methylation profiling.

Conclusions:

  • Effective analysis of Illumina BeadChip data is essential for advancing epigenetic research.
  • The outlined methods facilitate deeper understanding of DNA methylation in complex diseases.
  • This chapter serves as a valuable resource for researchers utilizing array-based epigenomic data.