<br>scGRN：人小鼠综合性单细胞基因调控网络平台,Nucleic Acids Research

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scGRN：人小鼠综合性单细胞基因调控网络平台
Nucleic Acids Research ( IF 16.6 ) Pub Date : 2023-10-27 , DOI: 10.1093/nar/gkad885
Xuemei Huang _{1,

2,

3,

4} , Chao Song _{1,

2,

4,

5} , Guorui Zhang _{1,

2,

4,

6} , Ye Li _{1,

2,

4,

6} , Yu Zhao _{1,

2,

3,

4} , Qinyi Zhang _{2,

6} , Yuexin Zhang _{1,

2,

4,

7} , Shifan Fan _{1,

2,

3,

4} , Jun Zhao ₁ , Liyuan Xie _{1,

2,

3,

4} , Chunquan Li _{1,

2,

3,

4,

8}

Affiliation

The First Affiliated Hospital & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases & College of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
School of Computer, University of South China, Hengyang, Hunan, 421001, China.
The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China.
Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
Hunan Provincial Maternal and Child Health Care Hospital, National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.

基因调控网络（GRN）是可解释的图模型，包含转录因子（TFs）与其下游靶基因之间的调控相互作用。理解 GRN 的拓扑结构和动力学对于解释疾病病因的机制和将相应的发现转化为新的疗法至关重要。单细胞多组学技术的最新进展促使以前所未有的分辨率从单细胞转录组学和表观基因组学数据中对 GRN 进行计算推断。在这里，我们介绍了 scGRN （https://bio.liclab.net/scGRN/），这是一个全面的人和小鼠单细胞多组学基因调控网络平台。当前版本的 scGRN 对 237 051 个细胞类型特异性 GRN（62 999 692 个 TF 靶基因对）进行了分类，涵盖 160 个组织/细胞系和 1324 个单细胞样品。scGRN 是第一个记录从单细胞多组学数据推断的不同人类和小鼠病症的大规模细胞类型特异性 GRN 信息的资源。我们已经实施了多种在线工具进行有效的 GRN 分析，包括差异 TF-目标网络分析、TF 富集分析和通路下游分析。我们还提供了有关 GRN 中靶基因的启动子、超级增强子和典型增强子与 TF 结合的详细信息。总之，scGRN 是一个集成且有用的平台，用于搜索、浏览、分析、可视化和下载感兴趣的 GRN，从而深入了解不同条件下调控机制的差异。

"点击查看英文标题和摘要"

scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse

Gene regulatory networks (GRNs) are interpretable graph models encompassing the regulatory interactions between transcription factors (TFs) and their downstream target genes. Making sense of the topology and dynamics of GRNs is fundamental to interpreting the mechanisms of disease etiology and translating corresponding findings into novel therapies. Recent advances in single-cell multi-omics techniques have prompted the computational inference of GRNs from single-cell transcriptomic and epigenomic data at an unprecedented resolution. Here, we present scGRN (https://bio.liclab.net/scGRN/), a comprehensive single-cell multi-omics gene regulatory network platform of human and mouse. The current version of scGRN catalogs 237 051 cell type-specific GRNs (62 999 692 TF–target gene pairs), covering 160 tissues/cell lines and 1324 single-cell samples. scGRN is the first resource documenting large-scale cell type-specific GRN information of diverse human and mouse conditions inferred from single-cell multi-omics data. We have implemented multiple online tools for effective GRN analysis, including differential TF–target network analysis, TF enrichment analysis, and pathway downstream analysis. We also provided details about TF binding to promoters, super-enhancers and typical enhancers of target genes in GRNs. Taken together, scGRN is an integrative and useful platform for searching, browsing, analyzing, visualizing and downloading GRNs of interest, enabling insight into the differences in regulatory mechanisms across diverse conditions.

更新日期：2023-10-27

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