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SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues
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),...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524591/ https://www.ncbi.nlm.nih.gov/pubmed/34634820 http://dx.doi.org/10.1093/nar/gkab881 |
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author | Qi, Changlu Wang, Chao Zhao, Lingling Zhu, Zijun Wang, Ping Zhang, Sainan Cheng, Liang Zhang, Xue |
author_facet | Qi, Changlu Wang, Chao Zhao, Lingling Zhu, Zijun Wang, Ping Zhang, Sainan Cheng, Liang Zhang, Xue |
author_sort | Qi, Changlu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8524591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85245912021-10-20 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 Nucleic Acids Res Database Issue 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. Oxford University Press 2021-10-11 /pmc/articles/PMC8524591/ /pubmed/34634820 http://dx.doi.org/10.1093/nar/gkab881 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Qi, Changlu Wang, Chao Zhao, Lingling Zhu, Zijun Wang, Ping Zhang, Sainan Cheng, Liang Zhang, Xue SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title | SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title_full | SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title_fullStr | SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title_full_unstemmed | SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title_short | SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |
title_sort | scovid: single-cell atlases for exposing molecular characteristics of covid-19 across 10 human tissues |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524591/ https://www.ncbi.nlm.nih.gov/pubmed/34634820 http://dx.doi.org/10.1093/nar/gkab881 |
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