Looplook: An integrative suite for target assignment and functional annotation of chromatin interactions empowered by expression-aware refinement and connected components clustering

Abstract

Deciphering target genes regulated by cis-regulatory elements (CREs) is critical for translating genetic and epigenomic findings into clinically actionable insights. However, linking distal CREs to their cognate target genes remains a fundamental challenge due to the limited availability of computational tools for spatial annotation and the oversimplified assignments inherent to conventional topology-only strategies. A flexible framework that integrates 3D proximity with transcriptional output is urgently needed. To address these limitations, we develop looplook, an integrated computational framework that bridges 3D chromatin topology with functional genomics to enable accurate, flexible, and user-driven CRE-target gene assignment. Looplook provides four core capabilities: (1) robust consensus building for denoising and consolidating replicated or multi-source chromatin loops by employing connected component clustering; (2) bidirectional spatial annotation between 3D chromatin loops and diverse linear genomic features, offering optional graph-based high-order discovery and a linear fallback for gapless network resolution; (3) an expression- or chromatin-aware refinement algorithm that selectively retains functional loops; and (4) automated downstream functional profiling seamlessly integrated with customizable multi-track visualization. Through case studies of the FOSL2 and BRD4 cistromes in liposarcoma cells, we demonstrate that looplook outperforms conventional linear annotation methods by integrating chromatin interactions with expression data and chromatin profiles, offering a powerful and valuable framework for distilling experimental omics data into functionally interpretable high-order gene regulation networks. looplook is freely available as an open-source R package, with source code and documentation hosted on GitHub, and will be distributed via the Bioconductor repository.