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Per public demand, we are hosting a 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 Ingenuity Pathway Analysis (IPA) and IPA Analysis Match Explorer feature. The trainer will walk through use cases in realms of 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.
This training will cover topics like
• How is a gene of interest expressed across different conditions?
• Is there a correlation in the expression of two genes or biomarkers of interest for a given condition?
• For a given condition of interest, can we derive a list of genes (example genes specific to a disease, treatment or cell type)?
• Can we generate custom cohorts of patients (example TP53 wt vs mutant or PDCD1 high vs low expression) and then generate survival curves representing those cohorts? Can we generate p-values to see if there is significant difference?
• Can we detect expression of a gene in different cell types from single cell data?
