Wang Chaochao, Huyan Ting, Guo Wuli, Shu Qi, Li Qi, Shi Jianyu
School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
Comput Struct Biotechnol J. 2024 Apr 25;23:1978-1989. doi: 10.1016/j.csbj.2024.04.057. eCollection 2024 Dec.
With both the advancement of technology and the decline in costs, single-cell transcriptomics sequencing has become widespread in the biomedical area in recent years. It can facilitate the pathogenic characteristics at the single-cell level, which will assist clinical researchers in exploring the mechanism of diseases. As a result, single-cell transcriptome data based on clinical samples grew exponentially. However, there is still a lack of a comprehensive database about immunocytes in inflammatory-associated diseases. To address this deficiency, we propose a human inflammatory-associated disease-based single-cell transcriptome database, NTCdb (www.ntcdb.org.cn). NTCdb integrates the open-source data of 1,023,166 cells derived from 11 tissues of 17 inflammatory-associated diseases in a uniform pipeline. It provides a set of analyzing results, including cell communication analysis, enrichment analysis, and Pseudo-Time analysis, to obtain various characteristics of immune cells in inflammatory-associated disease. Taking COVID-19 as a case study, NTCdb displays important information including potentially significant functions of certain cells, genes, and signaling pathways, as well as the commonalities of specific immunocytes between different inflammatory-associated disease.
随着技术的进步和成本的下降,近年来单细胞转录组测序在生物医学领域已广泛应用。它能够在单细胞水平上揭示致病特征,这将有助于临床研究人员探索疾病的发病机制。因此,基于临床样本的单细胞转录组数据呈指数级增长。然而,目前仍缺乏一个关于炎症相关疾病中免疫细胞的综合数据库。为了弥补这一不足,我们提出了一个基于人类炎症相关疾病的单细胞转录组数据库NTCdb(www.ntcdb.org.cn)。NTCdb通过统一的流程整合了来自17种炎症相关疾病的11个组织的1,023,166个细胞的开源数据。它提供了一系列分析结果,包括细胞通讯分析、富集分析和拟时间分析,以获取炎症相关疾病中免疫细胞的各种特征。以COVID-19为例,NTCdb展示了重要信息,包括某些细胞、基因和信号通路的潜在重要功能,以及不同炎症相关疾病中特定免疫细胞的共性。