Fig. 1: Overview of the SE-to-gene Links analysis.

This pipeline integrates RNA-seq and ChIP-seq datasets to derive insights into super-enhancer (SE) networks. The process begins with the extraction of gene expression profiles from RNA-seq data and the generation of peak regions and BAM files from ChIP-seq data using the nf-core packages⁵⁸. Subsequently, the peak-to-gene links (P2GL) analysis calculates correlation datasets between gene expression and ChIP-seq peak data. Simultaneously, the ChIP-seq peak and BAM data are processed using ROSE to identify super-enhancer regions, referred to as “ROSE SE.” The super-enhancer dataset is then refined by filtering it with the P2GL correlation data, resulting in a set of super-enhancers designated as “Filtered SE”. These filtered SEs, along with the P2GL correlation datasets, are utilized to construct an SE network graph, which provides deeper insights into SE-gene associations. Note that tools are denoted by circles. Aggregated individual datasets are depicted as overlapping squares, and cohesive data collections are represented by double-outlined squares.