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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.
Kim, M., Zheng, M., Tian, S. Z., Lee, B., Chuang, J. H., & Ruan, Y. (2019). MIA-Sig: Multiplex chromatin interaction analysis by signal processing and statistical algorithms. Genome Biology, 20(1). https://doi.org/10.1186/s13059-019-1868-z