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You may not have a typical transcriptomics dataset (i.e., a list of genes with differential expression), yet, you’d like to analyze a list of IDs. In this training, we will explore how to perform pathway and network analysis for lists of IDs in QIAGEN IPA.
Examples of lists that we’ll explore include:
• A gene/protein/metabolite list coming from a paper, generated in a lab or from a collaborator without differential expression
• A list of RS IDs for variants with or without numerical values such as p-values
• A list of proteins with Z-score (or other numerical value) calculated outside of IPA
• Other lists where you have mainly IDs and but no differential expression data
In this IPA training, you’ll learn how to:
• Upload and perform a pathway analysis (also known as core analysis) on a list of genes, proteins, metabolites or other types of IDs
• Open and investigate pathways and networks for understanding biological mechanisms
• Compare between analyses to identify similarities and differences for applications such as biomarker discovery
• Generate a custom network and contextualize it using public data
