Boosting the detection of enhancer-promoter loops via normalization methods for chromatin interaction data.

Abstract

Accurate detection of enhancer-promoter loops from genome-wide chromatin interaction data is critical for understanding gene regulation. Standard normalization methods, such as matrix balancing approaches, are widely used to correct biases in chromatin contact data prior to chromatin loop detection. However, while these methods preserve structural loop signals, they often attenuate enhancer-promoter interaction signals, making these regulatory loops more difficult to detect. To address this limitation, we develop Raichu, a normalization method for chromatin contact data. Raichu identifies nearly twice as many loops as conventional normalization approaches, recovering almost all previously detected loops while uncovering thousands of additional enhancer-promoter interactions that are otherwise missed. With its improved sensitivity for regulatory loops, Raichu detects more biologically meaningful differential interactions, including those between conditions within the same cell type. Moreover, Raichu performs robustly across a wide range of sequencing depths, resolutions, species, and experimental platforms, making it a versatile tool for revealing insights into three-dimensional genome organization and transcriptional regulation.