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Cancer outcome is influenced by both the tumor microenvironment and host immune response. Using QIAGEN OmicSoft Studio to access public data from The Cancer Genome Atlas (TCGA) and our human Single Cell Lands collection, you’ll learn how to:
• View host immune response clusters across TCGA samples
• Identify differentially expressed immunomodulators across sample groups
• Visualize single-cell dimension reduction maps and overlay expression data
• Identify potential biomarkers whose expression correlates or anti-correlates with target genes
• Validate new biomarkers using custom queries and TCGA survival data