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：

Dong, Fujuan;Li, Ye;Liu, Zhaomeng;Yu, Zhengmin;Qian, Fengcui;...

通讯作者：

Li, CQ

作者机构：

[Li, Lidong; Li, Chunquan; Qian, Fengcui; Yu, Zhengmin; Dong, Fujuan; Cai, Fuhong] Univ South China, Sch Comp, Hengyang, Hunan, Peoples R China.

[Li, Ye] Univ South China, Sch Basic Med Sci, Hengyang Med Sch, Dept Cell Biol & Genet, Hengyang, Hunan, Peoples R China.

[Liu, Zhaomeng] Univ South China, Hengyang Med Coll, Inst Biochem & Mol Biol, Hengyang, Hunan, Peoples R China.

[Li, Chunquan; Qian, Fengcui] Univ South China, Hunan Prov Key Lab Multiom & Artificial Intellige, Hengyang, Hunan, Peoples R China.

通讯机构：

[Li, CQ ] U

Univ South China, Sch Comp, Hengyang, Hunan, Peoples R China.

Univ South China, Hunan Prov Key Lab Multiom & Artificial Intellige, Hengyang, Hunan, Peoples R China.

语种：

英文

关键词：

Cell-type identification;scATAC-seq;Epigenetic regulation;Enrichment analysis

期刊：

PROCEEDINGS OF 2025 5TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND INTELLIGENT COMPUTING, BIC 2025

年：

2025

页码：

371-378

会议名称：

BIC '25: Proceedings of the 2025 5th International Conference on Bioinformatics and Intelligent Computing

会议地点：

Liaoning University, Shenyang, PEOPLES R CHINA

会议主办单位：

Liaoning University

出版地：

New York, NY, United States

出版者：

Association for Computing Machinery

ISBN：

9798400712203

DOI：

10.1145/3724979.3725036

基金类别：

Science and Technology Innovation Program of Hunan Province [2024RC1062]; National Natural Science Foundation of China [62171166, 62301246]; Innovation Platform and Talent Program [2023TP1047]; Natural Science Foundation of Hunan Province [20231130536]; University of South China [20224310NHYCG05]

机构署名：

本校为第一且通讯机构

院系归属：

药学与生物科学学院

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

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