Sign up to save your podcasts
Or
Share Single-cell RNA-seq, cell hashing, and spatial transcriptomics
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Single-cell RNA-seq, cell hashing, and spatial transcriptomics
A slide illustrating some of the many result types/graphics you will be able to generate after this training. https://qiagen.showpad.com/share/jYTCDPNfz1SdIMPQPSPYS
Analyze and interpret your own single-cell RNA-seq data using QIAGEN CLC Genomics Workbench, starting with either FASTQ or matrix files.
Learn how to perform the different steps of secondary analysis on your single-cell RNA-seq data, such as:
• Importing your raw FASTQ or processed cell-matrix files
• Using preconfigured but customizable pipelines/workflows for single-cell RNA-seq data.
• Generating high-resolution visuals and other files from your analysis, for publications and biopharmaceutical discoveries.
o Dimension reduction (UMAP, t-SNE) plots
o Differential expression tables for clusters, cell types or a combination of both
o Heat maps o Dot plots o Violin plots
• Using the “Create Cell Annotations from Hashtags” tool for cell hashing (e.g., CITE-seq).
• Applying spatial transcriptomic analysis, the latest feature in the single-cell RNA-seq module
View all episodes
By tv.qiagenbioinformatics.comA slide illustrating some of the many result types/graphics you will be able to generate after this training. https://qiagen.showpad.com/share/jYTCDPNfz1SdIMPQPSPYS
Analyze and interpret your own single-cell RNA-seq data using QIAGEN CLC Genomics Workbench, starting with either FASTQ or matrix files.
Learn how to perform the different steps of secondary analysis on your single-cell RNA-seq data, such as:
• Importing your raw FASTQ or processed cell-matrix files
• Using preconfigured but customizable pipelines/workflows for single-cell RNA-seq data.
• Generating high-resolution visuals and other files from your analysis, for publications and biopharmaceutical discoveries.
o Dimension reduction (UMAP, t-SNE) plots
o Differential expression tables for clusters, cell types or a combination of both
o Heat maps o Dot plots o Violin plots
• Using the “Create Cell Annotations from Hashtags” tool for cell hashing (e.g., CITE-seq).
• Applying spatial transcriptomic analysis, the latest feature in the single-cell RNA-seq module