This event has passed.
Start time where you are: Your time zone couldn't be detected. Try reloading the page.
You requested it, and we’re here to deliver. We’re excited to offer you comprehensive training on how to effectively use sample-level public data and metadata from sources like GEO, SRA, TCGA, GTEx, Blueprint, CCLE and other sources through QIAGEN Ingenuity Pathway Analysis (IPA) and the IPA Analysis Match Explorer feature. Your trainer will walk you through use cases in related to biomarker discovery, drug target investigation, studying survival in custom patient cohorts, multi-gene correlation and more.
Note: The word “condition” below refers to different diseases, disease subtypes, treatments, cell types, cell lines and more.
In this training, we’ll cover topics such as:
• How is a gene of interest expressed across different conditions?
• Is there a correlation in expression for two genes or biomarkers of user interest for a given condition?
• For a given condition of interest, can we derive a list of genes (for example, genes specific to a disease, treatment or cell type)?
• Can we generate custom cohorts of patients (for example, TP53 wt vs mutant or PDCD1 high vs low expression) and then generate survival curves representing those cohorts? Can we generate p-value to see if there is a significant difference?
• Recent update: Can we detect the expression of a gene in different cell types from single-cell data?
