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SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues
Nucleic Acids Research ( IF 16.6 ) Pub Date : 2021-10-04 , DOI: 10.1093/nar/gkab881
Changlu Qi 1 , Chao Wang 1 , Lingling Zhao 2 , Zijun Zhu 1 , Ping Wang 1 , Sainan Zhang 1 , Liang Cheng 1, 3 , Xue Zhang 3, 4
Affiliation  

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.

中文翻译:

SCovid:用于揭示 10 种人体组织中 COVID-19 分子特征的单细胞图谱

SCovid (http://bio-annotation.cn/scovid) 旨在提供全面的单细胞数据资源,用于揭示 2019 年冠状病毒病 (COVID-19) 在 10 个人体组织中的分子特征。COVID-19 是一种由严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 引起的流行病,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分子特征,研究关于 COVID-19 的研究已广泛开展,尤其是在单细胞分辨率下。然而,这些研究仍然相对独立和分散,限制了对病毒对多种组织影响的全面了解。为此,我们开发了 COVID-19 的单细胞图谱。首先,我们收集了 10 个人体组织中的 21 个 COVID-19 单细胞数据集,并与对照数据集配对。然后,我们构建了一条用于分析这些数据集的管道,以根据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 10 个人体组织中 21 个单细胞数据集的 1042227 个单细胞、11713 个稳定表达基因和 3778 个显着差异表达基因 (DEG)。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。当前版本的 SCovid 记录了 10 个人体组织中 21 个单细胞数据集的 1042227 个单细胞、11713 个稳定表达基因和 3778 个显着差异表达基因 (DEG)。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。当前版本的 SCovid 记录了 10 个人体组织中 21 个单细胞数据集的 1042227 个单细胞、11713 个稳定表达基因和 3778 个显着差异表达基因 (DEG)。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。
更新日期:2021-10-04
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