tetano
Editor, Senior Moderator
Nucleic Acids Res
. 2021 Oct 11;gkab881.
doi: 10.1093/nar/gkab881. Online ahead of print.
SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues
Changlu Qi[SUP] 1 [/SUP], Chao Wang[SUP] 1 [/SUP], Lingling Zhao[SUP] 2 [/SUP], Zijun Zhu[SUP] 1 [/SUP], Ping Wang[SUP] 1 [/SUP], Sainan Zhang[SUP] 1 [/SUP], Liang Cheng[SUP] 1 3 [/SUP], Xue Zhang[SUP] 3 4 [/SUP]
Affiliations
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.
. 2021 Oct 11;gkab881.
doi: 10.1093/nar/gkab881. Online ahead of print.
SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues
Changlu Qi[SUP] 1 [/SUP], Chao Wang[SUP] 1 [/SUP], Lingling Zhao[SUP] 2 [/SUP], Zijun Zhu[SUP] 1 [/SUP], Ping Wang[SUP] 1 [/SUP], Sainan Zhang[SUP] 1 [/SUP], Liang Cheng[SUP] 1 3 [/SUP], Xue Zhang[SUP] 3 4 [/SUP]
Affiliations
- PMID: 34634820
- DOI: 10.1093/nar/gkab881
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.