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10.1016/j.xpro.2022.101379 http://scihub22266oqcxt.onion/10.1016/j.xpro.2022.101379 35582459!9021126!35582459     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       STAR+Protoc 2022 ; 3 (2): 101379 Nephropedia Template TP {{tp|p=35582459|t=2022. Analyzing single cell transcriptome data from severe COVID-19 patients |pdf=|usr=}}{{35582459}} gab.com Text Analyzing single cell transcriptome data from severe COVID-19 patients JO: STAR Protoc http://www.kidney.de/pget.php?&tw=1&pmid=35582459 #FOAvip 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). Twit Text FOAVip Analyzing single cell transcriptome data from severe COVID-19 patients ????STAR Protoc http://www.kidney.de/pget.php?&tw=1&pmid=35582459 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35582459 #FOAvip English Wikipedia <ref>{{Cite pmid|35582459}}</ref> Analyzing single cell transcriptome data from severe COVID-19 patients #MMPMID35582459 Nassir N; Tambi R; Bankapur A; Karuvantevida N; Khansaheb HH; Zehra B; Begum G; Hameid RA; Ahmed A; Deesi Z; Alkhajeh A; Uddin KMF; Akter H; Safizadeh Shabestari SA; Gaudet M; Hachim MY; Alsheikh-Ali A; Berdiev BK; Al Heialy S; Uddin M STAR Protoc 2022[Jun]; 3 (2): 101379 PMID35582459show ga 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). |*COVID-19/genetics[MESH] |Biomarkers[MESH] |Humans[MESH]Analyzing single cell transcriptome data from severe COVID-19 patients(epmc).pdf DeepDyve Pubget Overpricing