Classification of Schizophrenia by Iterative Random Forest Feature Selection Based on DNA Methylation Array Data

Changes in DNA methylation are widely thought to be involved in the evolution of the disease, and most studies suggest that whole genome hypo-methylation levels are widespread in patients with schizophrenia. Since the exploration of DNA methylation changes in the etiology and pathogenesis of schizophrenia will be important for the prevention and early intervention, it is crucial to identify differentially methylated sites with high specificity and sensitivity for disease classification. In this study, we present a comprehensive approach MethIRF for the DNA methylation-based classification of schizophrenia by iterative random forest feature selection. The results show that MethIRF has a powerful discrimination ability compared to other four criteria methods for detecting differentially methylation sites. Moreover, the proposed method can discover significant CpG sites associated with schizophrenia and explore changes in the biological mechanisms of diseases.