Differential Gene Expression Analysis By R

RNA-Seq Analysis: A Comprehensive Guide for Biomedical Data

Unlock the power of RNA sequencing (RNA-Seq), a leading technology for understanding the dynamic cellular transcriptome. This course provides a complete introduction to RNA-Seq analysis, equipping you with the skills to analyze gene expression and identify differentially expressed genes (DE) across various biological conditions.

What you'll learn:

• RNA-Seq Fundamentals: Understand the principles of RNA-Seq and its applications in biomedical research.
• Differential Gene Expression (DGE): Master techniques for identifying genes with significant expression differences between groups.
• Bioinformatics with R and RStudio: Gain practical experience using R and RStudio for bioinformatics analysis. Learn to write and interpret code for RNA-Seq data.
• Data Visualization: Create insightful visualizations, including PCA plots, box plots, histograms, and heatmaps, to explore your data.
• Data Processing: Learn how raw RNA-Seq reads are processed, from SRA files to FASTQ files, and how to access the original data from the NCBI Gene Expression Omnibus (GEO) (accession number GSE52194).
• Complete Analysis Workflow: Perform end-to-end analysis of biomedical data using Galaxy and R.

Who is this course for?

This course is designed for all skill levels, even those with no prior programming or statistical background. We'll guide you through the process step-by-step, ensuring a successful learning experience. Comprehensive code and slides are provided to support your analysis.

Keywords: RNA-Seq, RNA sequencing, gene expression, differential gene expression, DGE, bioinformatics, R, RStudio, Galaxy, NCBI GEO, SRA, FASTQ, PCA, box plot, histogram, heatmap, transcriptome analysis, bioinformatics analysis.