Looplook: Integrating multiomics refinement and graph clustering for target assignment and functional inference of chromatin regulatory networks

Looplook accurately assigns target genes by integrating 3D chromatin topology with functional genomics, outperforming traditional methods in liposarcoma cells.

• Why it matters: Deciphering which genes are regulated by distal cis-regulatory elements is essential for translating genetic insights into clinical applications, but current tools lack spatial annotation and functional refinement.
• What they did: The framework employs connected component clustering, bidirectional spatial annotation, expression- or chromatin-aware refinement, and integrated functional profiling, tested on FOSL2 and BRD4 cistromes.
• The result: Looplook enhances gene regulation network interpretation by combining chromatin interactions with expression data, enabling more accurate, flexible, and high-order functional inference, and is openly available as an R package.