Identification Of Hub Genes In Pancreatic Cancer Using Rna Sequence Analysis

Gene expression microarrays have identified multiple tumor markers and therapeutic targets for pancreatic ductal adenocarcinoma (PDA). One of the most popular transcriptomics technologies is RNA sequencing (RNA-seq), which is useful for tumor diagnosis, prognosis, and treatment since it can show the connection between genetic mutation and intricate biolog-ical processes. Identification of aberrant transcriptions requires differential analysis of RNA-seq data, and effective methods for differential analysis include Limma, EdgeR, and DESeq2. The objective of this study is to perform an RNA-seq analysis using the DESeq2 package to find the hub genes that are associated with PDA. Here, we lay out a thorough procedure for using DESeq 2 to find genes that are differentially expressed (DEGs) between PDA tissues and healthy tissues, and the results are shown in volcano plots and heat maps. A total of 1596 DEGs (582 up-regulated and 1014 down-regulated) were identified. Further, these DEGs were analyzed for hub gene identification through the proteinprotein interaction (PPI) network, and we filtered the hub genes using the cytohubba plugin. In this study, we identified 7 hub genes that are significant in PDA, and the gene ontology (GO) and pathway analysis of the hub genes were also presented.