Ingenuity presents an analysis of lung adenocarcinomas with and without KRAS mutations in Ingenuity iReport and provides a demonstration of the statistical analysis and biological interpretation. The analysis strategies presented will be applied to RNA-Seq data made publicly available by Dr. Krishna Kalari at the Mayo Clinic. The webinar will be presented by Dr. Megan Laurance, Staff Scientist at Ingenuity Systems.

Megan demonstrates analysis strategies and best practices for identifying the most biologically-relevant genes from expression profiles of breast cancer cell lines. The analysis utilizes new tools and workflows in Ingenuity® iReport™ to help researchers rapidly identify subsets of differentially expressed genes connected to the functional endpoints and phenotypes most relevant to breast cancer subtypes, with an aim of identifying genes to take back to the lab for validation studies. The analysis strategies presented in this webinar can be applied to a variety of gene expression datasets, including RNA-Seq and microarray experiments.

This webinar uses previously published data from an influenza study to demonstrate the ability of Ingenuity® iReport™ to correctly identify expected results and gain additional novel biological insights from gene expression data. Lee et al. originally performed gene expression analysis on human type-I like alveolar epithelial cells that were mock infected or infected with seasonal H1N1or pandemic H1N1. Two separate iReport analyses were generated from this dataset: one comparing mock infection to seasonal H1N1 infection and another comparing mock infection to pandemic H1N1 infection. See how iReport expanded the insights described in the original publication and provided additional genes of interest for potential follow up studies in the areas of transcription and mRNA transport.

This webinar will introduce Ingenuity iReport and demonstrate how it can be used to get a rapid and accurate biological understanding of expression data coming straight off the machines, without using intermediary statistical software or bioinformatics tools. The example used is a cardiovascular dataset and we'll demonstrate how iReport can quickly help you identify genes and gene networks implicated in observed phenotypical changes.