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.
Agenda for Day 1 (Tuesday September 17th)
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
Agenda for Day 2 (Wednesday September 18th)
Gene Information, Pathway building, target characterization
This session will cover how to use IPA’s Knowledge Base for deep investigation of any gene, protein, or metabolite and how to further refine gene sets isolated from large scale data analyses.
- Search for a Gene/Chemical/function and drug
- Performing an Advanced Search: Limiting results to a molecule type, family or subcellular location.
- Add molecules from search results a pathway
- Understanding the legend
- General pathway navigating
- Using the pathway Build Tools
- Using the Overlay interpretation tools
Understanding IPA Statistics
- How is the Fisher’s Exact Test calculated
- How are z-scores calculated and what does it mean
Micro RNA and biomarkers in IPA
- This training session will focus on two advanced workflows: the biomarkers interpretation and the microRNA-mRNA interpretation. After this training session a user should be able to:
- Run a microRNA filter Analysis
- Filter the microRNA- targets relationship using a mRNA dataset.
- Explore the functional involvement of the microRNA’s targets within a Core analysis.
- Identify potential microRNA targets by using the pathway functionalities.
- Run and View a Biomarkers Filter Analysis
- Explore further the biomarkers result in pathway and list.
- Generate a Biomarker Filter comparison analysis.
If you plan to drive to the Fernwood building, you will need to park in the 6720C Parking Garage – Parking fees will be collected by cash or credit/debit card.
We apologize for any inconvenience this may cause. CIT Training recommends that NIH staff utilize the NIH Rockledge Shuttle from the Medical Center Metro to the Fernwood building, if at all possible, to avoid having to pay for parking. Exit the shuttle at the 6700B/Fernwood stop.