Modeling epigenetic modifications under multiple treatment conditions

ChIP–chip is a powerful tool for epigenetic research. However, current statistical methods are developed primarily for detecting transcription factor binding sites, and there is currently no satisfactory method for incorporating covariates such as time, hormone levels, and genotypes. In this study, we develop a varying coefficient model for epigenetic modifications such as histone acetylation and DNA methylation. By taking into account the special features of ChIP–chip data, a plug-in type method is derived for bandwidth selection in the local linear fitting of the varying coefficient model. Our results show that analyses using the proposed varying coefficient model can effectively detect diverse characteristics of epigenetic modifications over genomic regions as well as across different treatment conditions.