Registration required | Attendance in-person

Most omics (e.g., transcriptomics, proteomics, metabolomics) data analysis included a pathway enrichment analysis. These are redundant, as genes often participate in multiple pathways, biological processes, and other signatures. In addition, databases may organize pathways or biological processes hierarchically by including general and specific ones with many shared genes (e.g.,). Consequently, enrichment analysis often highlights several versions of the same pathway, biological process, etc. Collapsing redundant pathways into a single biological theme simplifies interpretation of results. Visualization can help identify the main biological themes and their relationships for in-depth study and experimental evaluation. During the session, we will use a tutorial dataset that will be made available to all the registrants.

The goals of the session are:

• Learn how to prepare enrichment analysis results for visualization on Enrichment Map
• Learn how to use Enrichment Map to visualize enrichment analysis results as a network.
• How to cluster and find main topics using AutoAnnotate.  
• Learn how to annotate clusters using WordCloud.

Requisite:

Download and install Cytoscape 

Attendees of this workshop may be interested in attending these:

Analysis of differential gene expression of bulk RNa-seq using "DESeq2" in RStudio