Abstract
The COVID-19 pandemic has led to a surge in transcriptomic studies investigating host immune responses to SARS-CoV-2. However, findings across studies vary due to differences in sample types, disease severity, and technical platforms. This project proposes a comprehensive meta-analysis of publicly available RNA-Seq datasets to integrate and harmonize transcriptomic data from COVID-19 patients. By applying robust statistical and bioinformatics pipelines, including batch effect correction, differential expression analysis, and pathway enrichment, the study aims to identify consistently dysregulated genes and pathways. Network-based analyses will be used to pinpoint central biomarkers and potential therapeutic targets. The integrative systems biology approach ensures greater statistical power and reproducibility, providing a foundation for biomarker-driven precision medicine strategies against COVID-19.
Keywords: COVID-19, RNA-Seq, meta-analysis, transcriptomics, biomarkers, therapeutic targets, host response, systems biology
Public Health Relevance
Identifying consistent host biomarkers and therapeutic targets across diverse populations enhances the global public health response to COVID-19. The study informs diagnostic and treatment strategies by revealing key molecular mechanisms of disease, supporting evidence-based resource allocation and intervention planning during pandemics.
The COVID-19 pandemic has led to a surge in transcriptomic studies investigating host immune responses to SARS-CoV-2. However, findings across studies vary due to differences in sample types, disease severity, and technical platforms. This project proposes a comprehensive meta-analysis of publicly available RNA-Seq datasets to integrate and harmonize transcriptomic data from COVID-19 patients. By applying robust statistical and bioinformatics pipelines, including batch effect correction, differential expression analysis, and pathway enrichment, the study aims to identify consistently dysregulated genes and pathways. Network-based analyses will be used to pinpoint central biomarkers and potential therapeutic targets. The integrative systems biology approach ensures greater statistical power and reproducibility, providing a foundation for biomarker-driven precision medicine strategies against COVID-19.
Keywords: COVID-19, RNA-Seq, meta-analysis, transcriptomics, biomarkers, therapeutic targets, host response, systems biology
Public Health Relevance
Identifying consistent host biomarkers and therapeutic targets across diverse populations enhances the global public health response to COVID-19. The study informs diagnostic and treatment strategies by revealing key molecular mechanisms of disease, supporting evidence-based resource allocation and intervention planning during pandemics.