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scEnrich: An online webserver for cell-type identification of scATAC-seq data through comprehensive region enrichment analysis

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成果类型:
会议论文
作者:
Fujuan Dong;Ye Li;Zhaomeng Liu;Zhengmin Yu;Fengcui Qian;...
作者机构:
[Zhaomeng Liu] Insititute of of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang, Hunan, China [email protected]
[Fujuan Dong; Zhengmin Yu; Fuhong Cai; Lidong Li] School of Computer, University of South China, Hengyang, Hunan, China [email protected]
School of Computer, University of South China, Hengyang, Hunan, China
Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, China [email protected]
[Ye Li] Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hengyang, Hunan, China [email protected]
语种:
英文
年:
2025
页码:
371-378
会议名称:
BIC '25: Proceedings of the 2025 5th International Conference on Bioinformatics and Intelligent Computing
出版地:
New York, NY, United States
出版者:
Association for Computing Machinery
ISBN:
9798400712203
机构署名:
本校为第一机构
摘要:
There are excellently annotated cell atlases for scRNA-seq currently, and there have been many works on cell type annotation of scRNA-seq data, and many methods have achieved good achievements. However, it has been noted that the extreme sparsity of scATAC-seq data often limits its power in cell-type identification. There are still few related algorithms available, and online cell type annotation tools are still lacking. The existing methods for annotating scATAC-seq rely too much on the scRNA-seq reference set, and the cell-type label accuracy needs to be improved. Therefore, we propose to us...

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