Bioinformatics Workshop Series - Session 7: Functional analysis of omics data: Overrepresentation Analysis (ORA) (In-Person)

Registration is required. View workshop details here.

The Bioinformatics Support Hub has designed this teaching series for researchers interested in learning the basic steps for re-analysis of publicly available bulk-RNAseq data. We will introduce you to basic genomic data annotation concepts, including where to find data to re-analyze, how to perform differential gene analysis, how to add gene annotations, and how to visualize your results. Finally, we'll demonstrate different approaches to performing gene pathway analysis. Importantly, we have introduced interspersed coached practice sessions in which attendees will be invited to participate. In these sessions, you will be able to try things for yourself and get immediate support if needed.

Details:

Target audience: These classes are meant for 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 a “first come, first served” basis.

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

Session 7. Functional analysis of omics data: Overrepresentation Analysis (ORA)

Attendance in person

High-throughput technologies (e.g., genomics, transcriptomics, proteomics) are widely used to monitor the activity of thousands of genes in a single experiment. These result in hundreds or thousands of differentially expressed genes leaving the researcher with the challenging task of understanding their biological relevance. Due to its simplicity, well-established statistical model, and ease of implementation, enrichment through Overrepresentation Analysis (ORA) is commonly used to interpret lists of differentially expressed genes and it is also available through many online tools. The goals of the session are:

• Learn what are the components of an ORA: gene list, cutoffs, background, or reference set, etc.
• Learn how to use three online tools: DAVID, WebGestalt, gProfiler
• Learn how to visualize and present the results