Epigenome-Wide Association Studies

Quantification Methods for Methylation Levels in Illumina Arrays.- Evaluating Reliability of DNA Methylation Measurement.- Accurate measurement of DNA methylation: Challenges and Bias Correction. Using R for Cell-Type Composition Imputation in Epigenome-Wide Association Studies.- Cell Type-Specific Signal Analysis in Epigenome-Wide Association Studies.- Controlling Batch Effect in Epigenome-Wide Association Study.- DNA methylation and Atopic Diseases.- Meta-analysis for Epigenome-Wide Association Studies.- Increase the Power of Epigenome-Wide Association Testing Using ICC-Based Hypothesis Weighting.- A Review of High-dimensional Mediation Analyses in DNA Methylation Studies.- DNA Methylation Imputation across Platforms.- Workflow to mine frequent DNA Co-Methylation Clusters in DNA Methylome Data.- BCurve: Bayesian Curve Credible Bands Approach for Detection of  Differentially Methylated Regions.- Predicting chronological age from DNA methylation data: A machine learning approach for small datasets and limited predictors.- Application of Correlation Pre-Filtering Neural Network to DNA Methylation Data: Biological Aging Prediction.- Differential Methylation Analysis for Bisulfite Sequencing (BS-seq) Data.