Differential Gene Expression Analysis: RNA-Seq in Human Cell Types

This report presents an analysis of RNA-Sequencing data to compare mRNA expression in three different human cell types: Total White Blood Cells, Purified B Cells, and Purified Granulocytes. The study focuses on identifying differentially expressed genes and clustering samples based on transcriptome similarity, utilizing the Galaxy web browser-based platform for bioinformatics tools. The workflow includes quality control of raw RNA-Seq data, read mapping using TopHat, transcript assembly with Cufflinks, and differential expression analysis using Cuffdiff. The analysis aims to identify genes that are differentially abundant in one cell type compared to others and to detect potential pathogens based on transcriptional activity. The conclusion suggests that gene expression varies among the cell samples, potentially indicating the presence of pathogens, and highlights the use of tools like MultiQC, FastQC, and Cufflinks for data analysis and comparison.