Registration Required -  *Attendance in person*

RNA-Seq is a powerful and widely used sequencing technique that enables the detection and quantification of messenger RNA molecules in a sample, providing valuable information about the genetic makeup and functional activity of cells in normal and pathological conditions. With the decreasing costs of sequencing and the growing availability of public RNA-seq datasets, the ability to analyze and interpret this type of data has become an increasingly important skill in the life sciences.

In this course, we will teach you the basics of analyzing bulk RNA-seq data using the open-source software RStudio and the popular package "DESeq2". Specifically, we will focus on performing differential gene expression analysis, which involves identifying genes that are differentially expressed between two or more conditions.

We will be using the GREIN (GEO RNA-seq Experiments Interactive Navigator) database, which contains a vast collection of RNA-seq datasets from various organisms and experimental conditions. By the end of the course, you will have gained hands-on experience in using RStudio and DESeq2 to perform differential gene expression analysis on RNA-seq data, and you will be able to apply these skills to your own research projects. Join us in this exciting opportunity to enhance your bioinformatics skills and unlock the potential of RNA-seq data!

This workshop is designed for: biomedical researchers with none to minimal knowledge of command language or R programming. Limited to 20 seats.

You will learn how to:

• Import data files into RStudio
• Load R packages
• Run “DESeq2”
• Save processed data files into your computer (e.g. normalized counts, DEX genes table)
• Perform basic data visualization (e.g. PCA plot, MA plot)

Requirements:

• Bring a laptop with R and RStudio installed and running.
• We will also provide you with the files of an RNA-seq dataset publicly available on NCBI’s GEO Datasets