Single-cell gene expression analysis starting from either FASTQ or expression data is now supported by QIAGEN CLC Genomics Workbench Premium, the scalable cross-platform desktop software for NGS data analysis. In this webinar, we will re-analyze data from a study on transcriptional profiling of the mouse heart (Skelly et al., 2018), starting from FASTQ and ending with detecting sexually dimorphic genes within different cell types.

Reference: Skelly, Daniel A., et al. (2018) Single-cell transcriptional profiling reveals cellular diversity and intercommunication in the mouse heart. Cell reports 22.3: 600-610.

Topics covered:
• Introduction to the QIAGEN CLC Genomics Workbench
• Generation of t-SNE and UMAP plots, starting from raw FASTQ read files
• Automated annotation of cell types using QIAGEN’s cell type classifier
• Detection of differentially expressed genes in different cell types in a case vs. control setting