QIAGEN CLC Genomics
Single-cell RNA-seq: Analysis and interpretation of user and public data - May 20 2021
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In this training, we will discuss:
• Generating visualizations for scRNA-seq data, starting with a read file (ex. FASTQ) or cell matrix file (ex. t-SNE plot, UMAP, heatmap, differential expression table, dot plot and more)
• Performing pathway analysis on scRNA-seq data to discover novel biological mechanisms, cell type-specific biomarkers and key regulators/targets
• Utilizing public scRNA-seq data from portals like GEO to identify and study cell clusters as well as verify biomarker and target expression
• Exporting results in both graphical and tabular formats
• The powerful knowledge bases backing these software
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