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SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues.
Qi, Changlu; Wang, Chao; Zhao, Lingling; Zhu, Zijun; Wang, Ping; Zhang, Sainan; Cheng, Liang; Zhang, Xue.
  • Qi C; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Wang C; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Zhao L; Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Zhu Z; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Wang P; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Zhang S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Cheng L; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
  • Zhang X; NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics, Harbin Medical University, Harbin, Heilongjiang 150028, China.
Nucleic Acids Res ; 50(D1): D867-D874, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1462427
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Databases, Factual / Single-Cell Analysis / COVID-19 Limits: Humans Language: English Journal: Nucleic Acids Res Year: 2022 Document Type: Article Affiliation country: Nar

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Databases, Factual / Single-Cell Analysis / COVID-19 Limits: Humans Language: English Journal: Nucleic Acids Res Year: 2022 Document Type: Article Affiliation country: Nar