Principle
Single-cell transcriptomics combines cell capture, barcoding and sequencing to resolve expression heterogeneity. It supports cell population identification, state comparisons, differentiation studies and cell communication analysis in complex tissues.
Applications
- Study tumor subpopulations and microenvironment composition
- Resolve state changes in neural, immune and other cell populations
- Explore differentiation trajectories and ligand-receptor communication
Method features
- Resolves heterogeneity obscured in bulk measurements
- Supports discovery of rare cell populations and candidate markers
- Cell preparation, viability and capture targets are assessed for each project
Workflow
- 01
Prepare and assess cells or nuclei
- 02
Capture cells, assign barcodes and reverse-transcribe RNA
- 03
Prepare libraries, sequence and generate expression matrices
- 04
Perform quality control, annotation and cell-state comparisons
This is a workflow overview. Experimental and analytical details depend on sample conditions and research objectives.