Spatial ChIP (ChIPSP), an R package for characterizing spatial gene regulation

ChIP-seq analysis is widely used to map transcription factor (TF) binding sites, but conventional downstream annotation commonly relies on linear genomic proximity and can miss candidate genes connected through three-dimensional (3D) chromatin architecture. This is particularly relevant for enhancer-promoter interactions that span large genomic distances via chromatin looping. To address this limitation, we developed ChIPSP, an R package that integrates ChIP-seq data with Hi-C chromatin loop interactions to prioritize candidate TF-associated genes within a 3D genomic context. We evaluated ChIPSP using the androgen receptor (AR) in LNCaP prostate cancer cells. ChIPSP identified 1,499 candidate AR-associated genes, of which 658 were missed by conventional linear annotation. Many of these genes were androgen-responsive by RNA-seq, and pathway analysis revealed enrichment in developmental transcriptional programs distinct from those captured by standard ChIP-seq. Individual loci, including KRT8 and MAF , were consistent with candidate long-range AR-associated regulation across chromatin loop boundaries. We further applied ChIPSP to glucocorticoid receptor (GR) ChIP-seq data in A549 lung cancer cells, where candidate gene targets such as IRS2 , UBL3 , and FOXO1 were identified and shown to be dexamethasone-responsive, providing a second nuclear-receptor example. ChIPSP extends ChIP-seq annotation into a spatial framework, supporting the prioritization of candidate TF-specific spatial associations. By bridging protein-DNA binding data with chromatin interaction maps, ChIPSP complements conventional peak-to-gene annotation and provides a practical tool for uncovering regulatory targets in cancer that are invisible to conventional approaches.