Biologically interpret RNAseq data with IPA

 
Sep 20, 2017 1:00 PM–2:00 PM (EDT)
Duration: 1hrs

In this webinar, we will show the Expression Analysis results generated from a QIAseq Targeted RNA-seq panel dataset. You can find out how to view and interpret your Expression Analysis results in IPA and learn about the multiple ways of relating the molecules in your dataset to the body of information in the Ingenuity Knowledge Base.

Discover more about:

  • Signaling and metabolic canonical pathways enriched in your data
  • Biological functions and diseases that are over-represented in your data
  • Predicted upstream regulators that may explain the expression changes observed in your data
  • How IPA's integration of analysis results creates causal hypotheses about how upstream regulators influence downstream phenotypes and biological functions
  • Interaction networks (algorithmically-generated pathways describing potential molecular interactions in your experimental system)
  • Molecules and biological processes that are predicted to be activated or inhibited in your experimental system

Lynne Mullen, Ph.D.

Dr. Lynne Mullen is a Senior Scientist within the Advanced Genomics Scientific and Technical Support team. Lynne completed her Ph.D. at Harvard University and continued to teach at Harvard after receiving her doctorate. Before her time at Harvard, she spent several years as a Research Scientist at Cedars-Sinai Prostate Cancer Center and at Quest Diagnostics. Additionally, Lynne has many years of experience conducting research to identify the genetic basis of human ophthalmic genetic disorders, working at the University of California at the Los Angeles Department of Ophthalmology and the University of Florida’s Department of Ophthalmology. Lynne has received numerous awards and fellowships from the National Science Foundation, the American Society of Mammologists and other esteemed institutions.