Publication: Determining Differentially Expressed Genes in Dengue Patients During Disease Progression
DOI
Type:
Article
Date
2024-05-15
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Humanities and Sciences, SLIIT
Abstract
Gene expression studies on gene transcription to synthesize functional gene products have been used
extensively to understand biological differences between different disease conditions. Thus, this study
determines differentially expressed genes in dengue infection during disease progression following
the three phases: Febrile, Defervescence and Convalescent. Integrative data analysis of two publicly
available longitudinal datasets in Gene Expression Omnibus (GEO) database has been employed to
accomplish the prime objective of exploring temporal gene expression patterns. The Friedman test
was given more emphasis due to the non-normality distributions of data. Repeated measures analysis
of variance (ANOVA) and linear mixed models were also implemented to examine the potential of
detecting differentially expressed genes despite non-normality. The Friedman test revealed significant
differences in gene expression levels across different phases in dengue disease over time. This led to
a notably higher count of genes showing differential expression compared to the other two methods:
Repeated measures ANOVA and linear mixed models. The pathway analysis approach consists
of significant differentially expressed genes derived from the Friedman test. The results identified
upregulated pathways with any significant change in the overall expression of genes within pathways
over time for the Febrile and Defervescence phases considering the Convalescent phase as a baseline.
Moreover, genes available in pathways were not identified by the two parametric tests for non-normal
data implying that the parametric approaches resulted in the least significance for data with non-normal
distributions.
Description
Keywords
Dengue, Friedman test, Gene expression studies, Longitudinal data, Non-normality
