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Positional effects revealed in Illumina methylation array and the impact on analysis
Chuan Jiao1, Chunling Zhang2, Rujia Dai1
1Center for Medical Genetics, Central South University, Changsha, Hunan 410012, PR China.
Epigenomics
|February 23, 2018
Summary
Positional effects significantly impact Illumina methylation array data, potentially altering results. The ComBat method is recommended for correcting these biases in methylation analysis.
Area of Science:
- Epigenetics
- Genomics
- Bioinformatics
Background:
- Illumina methylation beadchip arrays are widely used for epigenome-wide association studies.
- Potential technical artifacts, such as positional effects, can influence methylation measurements.
- Understanding and correcting these effects is crucial for accurate data interpretation.
Purpose of the Study:
- To investigate the existence and extent of positional effects in Illumina methylation data.
- To evaluate and identify an optimal method for correcting these positional effects.
Main Methods:
- Analysis of multiple Illumina methylation datasets (HumanMethylation450, HumanMethylation27, EPIC).
- Application of correction methods including ComBat, linear regression, functional normalization, and single-sample Noob.
- Evaluation of corrected data using four distinct assessment methods.
Main Results:
- A large number of CpG loci (52,988) were initially associated with sample positions.
- ComBat correction significantly reduced the number of positionally affected CpG loci to 112.
- Pre- and post-correction comparisons confirmed that positional effects can alter methylation values and downstream analysis outcomes.
Conclusions:
- Positional effects are a significant factor in Illumina methylation array data.
- These effects can introduce bias into methylation analyses.
- The ComBat method is recommended for effective correction of positional effects.
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