Dynamic changes in the three-dimensional (3D) organization of chromatin are associated with central biological processes, such as transcription, replication and development. Therefore, the comprehensive identification and quantification of these changes is fundamental to understanding of evolutionary and regulatory mechanisms. Here, we present Comparison of Hi-C Experiments using Structural Similarity (CHESS), an algorithm for the comparison of chromatin contact maps and automatic differential feature extraction. We demonstrate the robustness of CHESS to experimental variability and showcase its biological applications on (1) interspecies comparisons of syntenic regions in human and mouse models; (2) intraspecies identification of conformational changes in Zelda-depleted Drosophila embryos; (3) patient-specific aberrant chromatin conformation in a diffuse large B-cell lymphoma sample; and (4) the systematic identification of chromatin contact differences in high-resolution Capture-C data. In summary, CHESS is a computationally efficient method for the comparison and classification of changes in chromatin contact data.

染色质三维​​ (3D) 组织的动态变化与转录、复制和发育等核心生物过程相关。因此，对这些变化的全面识别和量化对于理解进化和调控机制至关重要。在这里，我们提出使用结构相似性 (CHESS) 的 Hi-C 实验比较，这是一种用于比较染色质接触图和自动差异特征提取的算法。我们证明了 CHESS 对实验变异的稳健性，并展示了其在以下方面的生物学应用：（1）人类和小鼠模型中同线性区域的种间比较；(2) Zelda 耗尽的果蝇胚胎中构象变化的种内鉴定；(3) 弥漫性大 B 细胞淋巴瘤样本中患者特异性的异常染色质构象；(4) 高分辨率 Capture-C 数据中染色质接触差异的系统识别。总之，CHESS 是一种计算高效的方法，用于对染色质接触数据的变化进行比较和分类。