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An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies
Michiel E Adriaens1, Magali Jaillard, Lars M T Eijssen
1Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands. michiel.adriaens@maastrichtuniversity.nl
BMC Genomics
|January 27, 2012
Summary
T-quantile normalization and Tukey's biweight scaling are superior for analyzing DNA methylation and protein binding data from regulation microarrays. These methods preserve signal separation and improve data comparability for reliable downstream analysis.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Chromatin immunoprecipitation with microarray technology (ChIP-on-chip) enables genome-wide mapping of DNA-interacting proteins and DNA methylation sites.
- These techniques are crucial for understanding gene transcription regulation.
- Traditional transcriptomics microarray data pre-processing may not be suitable for regulation microarrays due to differences in goals, sample preparation, and design.
Purpose of the Study:
- To evaluate the performance of various normalization approaches for regulation microarrays.
- To identify normalization methods that effectively make data quantitatively comparable while preserving the distinction between enriched and un-enriched probe signals.
Main Methods:
- Comparison of widely used normalization methods including VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, and Peng's method.
- Application of these methods to diverse regulation microarray datasets (DNA methylation, transcription factor binding, histone modification).
- Assessment of normalization performance by analyzing data distributions and the ability to identify known enriched genomic regions.
Main Results:
- Significant performance differences were observed among the evaluated normalization procedures.
- T-quantile normalization (applied separately on channels) and Tukey's biweight scaling demonstrated superior performance.
- These methods effectively conserved the separation between enriched and un-enriched signals and improved the identification of known enriched regions.
Conclusions:
- T-quantile normalization and Tukey's biweight scaling are recommended for regulation microarrays.
- T-quantile normalization offers the additional benefit of improved inter-microarray comparability.
- Popular methods like quantile, LOWESS, Peng's, and VSN can substantially impact the reliability of downstream analyses by altering data distributions.
