College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
Nucleic Acids Res. 2022 Jan 7;50(D1):D867-D874. doi: 10.1093/nar/gkab881.
SCovid (http://bio-annotation.cn/scovid) aims at providing a comprehensive resource of single-cell data for exposing molecular characteristics of coronavirus disease 2019 (COVID-19) across 10 human tissues. COVID-19, an epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been found to be accompanied with multiple-organ failure since its first report in Dec 2019. To reveal tissue-specific molecular characteristics, researches regarding to COVID-19 have been carried out widely, especially at single-cell resolution. However, these researches are still relatively independent and scattered, limiting the comprehensive understanding of the impact of virus on diverse tissues. To this end, we developed a single-cell atlas of COVID-19. Firstly we collected 21 single-cell datasets of COVID-19 across 10 human tissues paired with control datasets. Then we constructed a pipeline for the analysis of these datasets to reveal molecular characteristics of COVID-19 based on manually annotated cell types. The current version of SCovid documents 1 042 227 single cells of 21 single-cell datasets across 10 human tissues, 11 713 stably expressed genes and 3778 significant differentially expressed genes (DEGs). SCovid provides a user-friendly interface for browsing, searching, visualizing and downloading all detailed information.
SCovid(http://bio-annotation.cn/scovid)旨在提供一个全面的单细胞数据资源,以揭示 2019 年冠状病毒病(COVID-19)在 10 个人体组织中的分子特征。COVID-19 是由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的传染病,自 2019 年 12 月首次报告以来,已被发现伴有多器官衰竭。为了揭示组织特异性的分子特征,针对 COVID-19 的研究已经广泛开展,尤其是在单细胞分辨率水平。然而,这些研究仍然相对独立和分散,限制了对病毒对不同组织影响的全面理解。为此,我们开发了 COVID-19 的单细胞图谱。首先,我们收集了 COVID-19 在 10 个人体组织中的 21 个单细胞数据集,并与对照数据集配对。然后,我们构建了一个分析这些数据集的流程,以基于手动注释的细胞类型揭示 COVID-19 的分子特征。当前版本的 SCovid 记录了 21 个人体组织的 21 个单细胞数据集的 1 042 227 个单细胞、11 713 个稳定表达的基因和 3778 个显著差异表达的基因(DEGs)。SCovid 提供了一个用户友好的界面,用于浏览、搜索、可视化和下载所有详细信息。