Single-cell technologies have improved in their capabilities to study the changes in cellular expression at the genome, epigenome, proteome, transcriptome, and metabolome level. They can now be used to resolve differences in cell type and cell state, making them ideal tools for gaining insight into cell diversity and biological heterogeneity. When coupled with spatial techniques, single-cell analysis can shed light on cellular interactions and dynamics, as well as on cell-specific responses and vulnerabilities. This Bench Tips webinar will feature early-career scientists who will share best practices and technical know-how gained from many carefully designed and successfully executed experiments.
In this webinar, you will learn about
- When to use single-cell analysis and where it provides maximum ROI
- Rationale for when to use single-cell versus single-nuclei analysis
- Optimization of sample prep and experimental design for single-cell analysis
- Working with challenging sample types
- Analysis and integration of single-cell data with spatial transcriptomics
- Common challenges and how to overcome them
- Case studies describing how single-cell analysis can be used for diverse applications
Researchers interested in the following should attend
- Single-cell and single-nuclei analysis
- RNA and ATAC sequencing
- Spatial transcriptomics
- Gene expression profiling
- Functional genomics, proteomics, transcriptomics, and epigenomics
- Cellular and spatial analysis for organs like the eye
- Data visualization and integration