Analyzing single cell transcriptome data from severe COVID-19 patients

Autor: Nasna Nassir, Richa Tambi, Asma Bankapur, Noushad Karuvantevida, Hamdah Hassan Khansaheb, Binte Zehra, Ghausia Begum, Reem Abdel Hameid, Awab Ahmed, Zulfa Deesi, Abdulmajeed Alkhajeh, K.M.Furkan Uddin, Hosneara Akter, Seyed Ali Safizadeh Shabestari, Mellissa Gaudet, Mahmood Yaseen Hachim, Alawi Alsheikh-Ali, Bakhrom K. Berdiev, Saba Al Heialy, Mohammed Uddin
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: STAR Protocols, Vol 3, Iss 2, Pp 101379- (2022)
Druh dokumentu: article
ISSN: 2666-1667
DOI: 10.1016/j.xpro.2022.101379
Popis: Summary: We describe the protocol for identifying COVID-19 severity specific cell types and their regulatory marker genes using single-cell transcriptomics data. We construct COVID-19 comorbid disease-associated gene list using multiple databases and literature resources. Next, we identify specific cell type where comorbid genes are upregulated. We further characterize the identified cell type using gene enrichment analysis. We detect upregulation of marker gene restricted to severe COVID-19 cell type and validate our findings using in silico, in vivo, and in vitro cellular models.For complete details on the use and execution of this protocol, please refer to Nassir et al. (2021b).
Databáze: Directory of Open Access Journals