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In this session, we will use the results of a differential expression analysis of RNA-se data to generate an interaction network. As a result of the differential analysis, the researcher may be left with a list of dozens or hundreds of genes. In addition to finding pathways and biological processes through overrepresentation analysis, understanding the interaction between the differentially regulated genes may provide additional functional clues (e.g. clusters, hubs) in the data. In this section, we will take the results of a differential analysis from RNA-seq data and will generate an interaction network using a STRING knowledgebase. This network will then be used for further analysis (e.g. functional clusters, hubs). Attendees of this session will learn:
-how to generate an interaction network using a list of differentially expressed genes or proteins
-how to visualize this network using Cytoscape
-overlaying and visualizing expression data on the resulting network.
-how to find and functionally annotate clusters, and hubs.