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An effective processing pipeline for harmonizing DNA methylation data from Illumina's 450K and EPIC platforms for
Lauren A Vanderlinden1, Randi K Johnson2, Patrick M Carry2
1Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
BMC Research Notes
|September 9, 2021
Summary
Harmonizing DNA methylation data from Illumina 450K and EPIC arrays requires careful preprocessing. Normalization, probe filtering, and meta-analysis are key to addressing platform variability in large epidemiological studies.
Area of Science:
- Epigenetics
- Bioinformatics
- Epidemiology
Background:
- Illumina BeadChip arrays (450K and EPIC) are widely used for DNA methylation profiling in large epidemiological studies.
- Technological advancements and platform differences (450K vs. EPIC) introduce variability, complicating data harmonization.
- Existing preprocessing pipelines do not fully account for inter-platform technical variability.
Purpose of the Study:
- To evaluate preprocessing tools for harmonizing DNA methylation data across Illumina 450K and EPIC platforms.
- To assess the impact of quality control, normalization, batch effect adjustment, and genomic inflation on data harmonization.
- To develop guidelines for harmonizing data from different Illumina methylation array platforms.
Main Methods:
- Systematic evaluation of various preprocessing tools at each step of the DNA methylation data pipeline.
- Utilized 450K and EPIC array data from the Diabetes Autoimmunity Study in the Young (DAISY) cohort.
- Applied meta-analysis to account for platform variability and corrected for genomic inflation.
Main Results:
- Normalization and probe filtering demonstrated the most significant impact on data harmonization.
- Meta-analysis proved an effective and accessible method for managing platform variability.
- Correction for genomic inflation further improved data harmonization.
Conclusions:
- Normalization, probe filtering, and meta-analysis are critical for harmonizing 450K and EPIC DNA methylation data.
- Technical replicates are valuable for assessing preprocessing steps.
- Guidelines are provided for effective data harmonization in multi-platform epidemiological studies.
