Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health threat globally. To discover key molecular changes in COVID-19 and its secondary complications, we analyzed next-generation sequencing (NGS) data of COVID-19. NGS data (GSE163151) was screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were identified in the present study, using DESeq2 package in R programming software. Gene ontology (GO) and pathway enrichment analysis were performed, and the protein-protein interaction (PPI) network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network were established. Subsequently, receiver operating characteristic curve (ROC) analysis was used to validate the diagonostics valuesof the hub genes. Firstly, 954 DEGs (477 up regulated and 477 down regulated) were identified from the four NGS dataset. GO enrichment analysis revealed enrichment of DEGs in genes related to the immune system process and multicellular organismal process, and REACTOME pathway enrichment analysis showed enrichment of DEGs in the immune system and formation of the cornified envelope. Hub genes were identified from the PPI network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Furthermore, the ROC analysis indicate that COVID-19 and its secondary complications with following hub genes, namely, RPL10, FYN, FLNA, EEF1A1, UBA52, BMI1, ACTN2, CRMP1, TRIM42 and PTCH1, had good diagnostics values. This study identified several genes associated with COVID-19 and its secondary complications, which improves our knowledge of the disease mechanism.
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health threat globally. To discover key molecular changes in COVID-19 and its secondary complications, we analyzed next-generation sequencing (NGS) data of COVID-19. NGS data (GSE163151) was screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were identified in the present study, using DESeq2 package in R programming software. Gene ontology (GO) and pathway enrichment analysis were performed, and the protein-protein interaction (PPI) network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network were established. Subsequently, receiver operating characteristic curve (ROC) analysis was used to validate the diagonostics valuesof the hub genes. Firstly, 954 DEGs (477 up regulated and 477 down regulated) were identified from the four NGS dataset. GO enrichment analysis revealed enrichment of DEGs in genes related to the immune system process and multicellular organismal process, and REACTOME pathway enrichment analysis showed enrichment of DEGs in the immune system and formation of the cornified envelope. Hub genes were identified from the PPI network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Furthermore, the ROC analysis indicate that COVID-19 and its secondary complications with following hub genes, namely, RPL10, FYN, FLNA, EEF1A1, UBA52, BMI1, ACTN2, CRMP1, TRIM42 and PTCH1, had good diagnostics values. This study identified several genes associated with COVID-19 and its secondary complications, which improves our knowledge of the disease mechanism.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.