and colleagues also uses DHS profiles, but additionally incorporates genome-wide expression data [70]. Rather than employing a fixed distance-based model, Shen and colleagues apply chromatin conformation data from Hi-C experiments to guide the association of enhancers to genes marked by H3K4me1, H3K27ac and RNA Pol II [67]. As an alternative to methods based on chromatin structure, Andersson and colleagues leverage cap analysis of gene expression (CAGE) data to correlate transcription at enhancers with gene expression [16]. There are two computational approaches that are publicly available and executable through website or command-line programs: predicting specific tissue interactions of genes and enhancers (PreSTIGE) [7] and integrated methods for predicting enhancer targets (IM-PET) [69]. PreSTIGE identifies enhancers and genes that demonstrate quantitative cell-type specificity based on H3K4me1 and RNA sequencing (RNA-seq), and can process data from human and mouse cell types [68]. IM-PET, like previously discussed methods, considers the proximity of an enhancer to potential gene targets and the correlation of enhancer and promoter activity, along with measures of transcription factor activity and evolutionary conservation.Table 1 Computational approaches to predicting gene targets of enhancer elements Reference or method Input data required Gene expression Linear model Number of genes with predictions (per cell line)
