The single-molecule multiplex chromatin interaction data are generated by emerging 3D genome mapping technologies such as GAM, SPRITE, and ChIA-Drop. These datasets provide insights into high-dimensional chromatin organization, yet introduce new computational challenges. Thus, we developed MIA-Sig, an algorithmic solution based on signal processing and information theory. We demonstrate its ability to de-noise the multiplex data, assess the statistical significance of chromatin complexes, and identify topological domains and frequent inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains. Together, MIA-Sig represents a novel algorithmic framework for multiplex chromatin interaction analysis.

中文翻译：

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MIA-Sig：通过信号处理和统计算法进行多重染色质相互作用分析

单分子多重染色质相互作用数据由新兴的 3D 基因组作图技术（例如 GAM、SPRITE 和 ChIA-Drop）生成。这些数据集提供了对高维染色质组织的见解，但也带来了新的计算挑战。因此，我们开发了 MIA-Sig，一种基于信号处理和信息论的算法解决方案。我们展示了它对多重数据进行去噪、评估染色质复合物的统计显着性以及识别拓扑域和频繁的域间接触的能力。在染色质免疫沉淀 (ChIP) 富集数据上，MIA-Sig 可以清楚地区分蛋白质相关相互作用与非特异性拓扑结构域。MIA-Sig 代表了一种用于多重染色质相互作用分析的新颖算法框架。