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Workshop Series: Introduction to bulk RNA-seq analysis - from counts to functional analysis 

Summary:

The Bioinformatics Support Hub has designed this hands-on teaching series for researchers interested in learning the basics steps for re-analysis of publicly available bulk-RNAseq data. Over the next two months, you can learn basic concepts concerning genomic data annotation and vocabulary, where to find bulk RNAseq data to re-analyze, how to perform differential gene analysis in RStudio and with point-click proprietary software, how to visualize your results, how to find transcription factors that may be regulating differentially expressed genes, and finally different approaches to perform gene pathway analysis. *Registrations for October sessions will open at the end of September.

Session 3. Upload bulk RNAseq data tables into RStudio and setup a DESeq2 analysis

Sequencing data is increasingly available in public repositories making it easier for reanalysis. Join us for the first part on how to run a differential gene expression analysis with *DESeq2.

In this session you will learn how to import tables containing the raw counts and metadata of a publicly available bulk-RNA seq dataset and setup a differential gene expression analysis using the R package DESeq2.  

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

You will learn how to:

• Use R packages *readr* to import data tables into RStudio
• Use basic R functions such as *view()* and *str()* to visualize and inspect data
• Import R package *DESeq2* into RStudio
• Assemble a DESeq2 data frame and design a differential gene expression analysis
• Run the function *DESeq()* and brief introduction to the function *results()*

If you are interested in understanding how to extract DESeq2 results when you have more than 2 groups to compare, consider attending session 4 of this series.

Details:

Target audience: These classes are meant to novices in bulk RNAseq analysis, with none to minimal knowledge in R programming.

Seating – in person classes are limited to 16 places.

Registrations - open to all interested. However, seating will be on “first come, first served” basis.

Recording – we will record the sessions so you can follow asynchronously.

Series Program: