75 / 2024-10-19 11:42:35
DiffDomain enables identification of structurally reorganized topologically associating domains
Topologically associating domain,Differential analysis,Hi-C,single-cell Hi
Abstract Accepted
田德朝 / 中山大学
The three-dimensional organization of the genome plays a crucial role in gene regulation, and topologically associating domains (TADs) are key structural components of this organization. Reorganizations of TADs between different biological states, such as health and disease, are linked to important genomic functions. In this talk, I will present DiffDomain, a new algorithm that leverages high-dimensional random matrix theory to identify reorganized TADs using high-throughput chromosome conformation capture (Hi-C) data and scHi-C data. Benchmarking DiffDomain against existing methods demonstrates superior performance in detecting biologically relevant TAD reorganizations while maintaining lower false positive rates and higher true positive rates. Additionally, we introduce a new subtype of reorganized TADs uncovered through DiffDomain. Applying this method to both bulk and single-cell Hi-C data reveals associations betweeenTAD reorganization and structural variations and epigenomic changes, including altered CTCF binding patterns. Moreover, the method can robustly identify reorganized TADs using pseudo-bulk Hi-C data from as few as 100 cells per condition, providing insights into cell-to-cell variability and heterogeneity of TADs.
Important Date
  • Conference Date

    Oct 31

    2024

    to

    Nov 03

    2024

  • Nov 03 2024

    Registration deadline

Sponsored By
崖州湾国家实验室
华中农业大学
浙江大学
中国遗传学会
中国遗传学会三维基因组学专委会
Organized By
中国生物信息学基因组信息学专委会
中国遗传学会表观遗传分会
中国细胞生物学学会染色质生物学分会
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