Ingenuity Pathways Analysis (IPA) is software that helps researchers model, analyze, and understand the complex biological and chemical systems at the core of life science research.
This training session will cover:
Large Scale (gene expression, proteomics, Metabolomics) Data Analysis
Using an example gene expression dataset the basic to intermediate IPA functionalities will be covered.
Upload single and multiple observation datasets
Microarray, RNAseq, proteomic, miRNA, metabolite data
- Find and interpret the most relevant processes and disease associated with your data
- Find and interpret the most relevant canonical pathway
- Identify predicted upstream regulators (transcription factors, miRNA, receptors, drugs, etc.)
- Understand the basics of the Network generation algorithm and how to interpret/modify the network result
Comparing Large Data sets and results
Using an example microarray datasets, methods for comparing core analysis results and gene lists will be discussed. In addition, we will discuss integrating multiple experimental platforms such as microarray, SNPs, proteomics, etc.
- Comparing IPA core analysis results
- Comparing datasets, gene lists, and members of a core analysis
- Using the expression bar-chart overlay option
- Integrate multiple experimental platforms together