Multiplex chromatin interaction analysis by signal processing and statistical algorithms
Minji KimiD, Meizhen ZhengiD, Simon Zhongyuan TianiD, Daniel Capurso, Byoungkoo LeeiD, Jeffrey H. ChuangiD, Yijun RuaniD
Abstract
The single-molecule multiplex chromatin interaction data generated by emerging non-ligation-based 3D genome mapping technologies provide novel insights into high dimensional chromatin organization, yet introduce new computational challenges. We developed MIA-Sig (https://github.com/TheJacksonLaboratory/mia-sig.git), an algorithmic framework to de-noise the data, assess the statistical significance of chromatin complexes, and identify topological domains and inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains.
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