Gene Expression Visualization
The visualization module allows you to explore gene expression patterns across your single-cell dataset by plotting specific genes of interest in reduced dimensional space (UMAP or PCA).
Step-by-Step Visualization Process
Follow these steps to visualize gene expression:
- (1) Select Dimension Reduction: Choose between UMAP or PCA for your visualization space
- (2) Search Genes: Type the genes of interest in the search field
- (3) Review Selection: The selected genes will appear on the right side for confirmation
- (4) Run Analysis: Click on Run to start the visualization process
- (5) Continue: Click on Continue to Results to proceed to the download section
Gene Selection and Biological Markers
For this tutorial, we select PTPRC, CD8A, and CD4, which are well-known cellular markers:
- PTPRC (CD45): Pan-immune cell marker expressed by all immune cells
- CD8A: Specific marker for CD8+ T cells (cytotoxic T lymphocytes)
- CD4: Specific marker for CD4+ T cells (helper T cells)
These markers are excellent examples for demonstrating immune cell identification and characterization in single-cell datasets. You can search for any genes of interest relevant to your research question.
Understanding Visualization Results
After running the visualization, you will see gene expression plots overlaid on your chosen dimensional reduction space. Each plot shows:
- Cell positions: Based on UMAP or PCA coordinates
- Expression levels: Represented by color intensity
- Spatial patterns: Revealing which cell populations express your genes of interest
This spatial representation helps identify cell types, validate clustering results, and understand the biological context of your single-cell data.
