Tutorials
Single-cell RNA-seq data analysis and interpretation
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In this 90-minute training, attendees will learn how to:
• Start with fastq, cell matrix file and/or differential expression file for scRNA-seq data
• Per user preference, either automate or customize their analysis pipeline/workflow
• Easily generate visualizations such as t-SNE, UMAP, heatmap, differential expression table, dot plots and more
• Upload differential expression data to QIAGEN IPA (either from CLC or from another source)
• Perform pathway analysis on scRNA-seq data and compare different clusters to discover novel biological mechanisms, cell type-specific biomarkers and key regulators/targets
• Export results in the form of highquality images or tabular format
Speaker: Araceli Cuellar, Field Application Specialist, QIAGEN Digital Insights
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