An Effective Tool for Differential Interaction Analysis in Single-Cell Hi-C Data

The three-dimensional (3D) genome refers to exploring the spatial arrangement of chromatins within the cell nucleus. Analyzing differential interactions, the basic units of the 3D genome, particularly at the single-cell level, is crucial for revealing cell-type-specific functions and states. However, the sparsity and heterogeneity of single-cell 3D genome data pose significant challenges. Although existing methods offer helpful solutions, most of them lack the design for data distribution and cell-specific characteristics. Here, we developed a new method, DISHIC, for identifying differential interactions in single-cell high-throughput Chromatin Conformation Capture (scHi-C) data. Based on the ZINB-WaVE model, DISHIC independently models each bin pair, accounting for both bin-pair-level and cell-level covariates. We validated DISHIC's effectiveness and demonstrated its enhanced effectiveness compared to other methods. The code is available at https://github.com/zhaoyichao777/DISHIC.