The Differentially Expressed Genes and Biomarker Identification for Dengue Disease Using Transcriptome Data Analysis
Author(s): Sunil Krishnan G*
This bioinformatics and biostatistics study was designed to recognize and examine the differentially expressed genes (DEGs) linked with dengue virus infection in Homo sapiens. Thirty nine transcriptome profile datasets were analyzed by linear models for microarray analysis based on the R package of the biostatistics test for the identification of significantly expressed genes associated with the disease. The Benjamini and Hochberg (BH) standard operating procedure assessed DEGs had the least false discovery rate and chosen for further bioinformatics gene analysis. The large gene dataset was investigated for systematically extracting the biological significance of DEGs. Four clusters of DEGs were distinguished from the dataset and found the extracellular calcium sensing receptor gene expressing CASR protein was the most connecting human protein in the disease progression and discovered this protein as a potential biomarker for acute dengue fever.