Take your IPA analysis results to the next level by comparing them to your own analyses or from a library of over 100k pre-computed datasets to find similar or opposite biological signatures. Identify key genes or entities and then explore how they are expressed across normal tissues, diseases and more from over 600k biological samples to gain deep context.



Attendees will learn how to:

• Advance insights with the IPA Analysis Match comparison feature to compare large numbers of user datasets and/or public datasets (from GEO, SRA, cancer collections and more)

• Use and interpret the IPA Activity Plot feature to identify key genes and regulators common across datasets

• Explore identified key genes in Land Explorer to query and visualize expression across tissues, disease states, mutation status, including survival curves



Specific IPA analyses to be featured include:

• Analysis Match

• Activity Plot

• Pattern Search

• QIAGEN OmicSoft Land Explorer

• Graphical Summary of analysis results

• Among others