Abstract PAGER-CoV ( http://discovery.informatics.uab.edu/PAGER-CoV/ ) is a new web-based database that can help biomedical researchers interpret coronavirus-related functional genomic study results in the context of curated knowledge of host viral infection, inflammatory response, organ damage, and tissue repair. The new database consists of 11 835 PAG s ( P athways, A nnotated gene-lists, or G ene signatures) from 33 public data sources. Through the web user interface, users can search by a query gene or a query term and retrieve significantly matched PAGs with all the curated information. Users can navigate from a PAG of interest to other related PAGs through either shared PAG-to-PAG co-membership relationships or PAG-to-PAG regulatory relationships, totaling 19 996 993. Users can also retrieve enriched PAGs from an input list of COVID-19 functional study result genes, customize the search data sources, and export all results for subsequent offline data analysis. In a case study, we performed a gene set enrichment analysis (GSEA) of a COVID-19 RNA-seq data set from the Gene Expression Omnibus database. Compared with the results using the standard PAGER database, PAGER-CoV allows for more sensitive matching of known immune-related gene signatures. We expect PAGER-CoV to be invaluable for biomedical researchers to find molecular biology mechanisms and tailored therapeutics to treat COVID-19 patients.
【초록키워드】 COVID-19, viral infection, Molecular biology, Therapeutics, knowledge, database, Regulatory, Viral, Data analysis, case study, information, genomic, enrichment analysis, mechanism, tissue repair, COVID-19 patients, Inflammatory response, data set, user interface, user, gene set enrichment analysis, help, treat, organ damage, Gene Expression Omnibus, RNA-seq data, GSEA, researcher, Host, gene signatures, Genes, performed, significantly, subsequent, functional, curated, 【제목키워드】 coronavirus disease, Pathways, gene signature,