Find variable genes

Identifying variable genes in single-cell data is essential for highlighting features that distinguish different cell populations. This involves statistical methods to detect genes that exhibit significant variability across cells, beyond what is expected by technical noise. Advanced computational tools like Seurat or Scanpy implement these approaches, allowing researchers to focus on genes that are likely to be biologically informative. This step is crucial for downstream analyses such as clustering and identifying cell types based on gene expression profiles.

We use the tool “Scanpy FindVariableGenes” in this workflow to find varaible genes in our single-cell RNA-seq dataset.

For users running the workflow -

• In the workflow, you don’t need to enter any values. All values are default. Use the edit button next to the parameter you would like to change. You are ready to move on to the next step

For users running each step -

• Open the tool “Scanpy FindVariableGenes”

• The tool parameters are default and you can change them according to your preferences. Click on “Execute”