What are Marker Genes?¶
For each factor in a dataset, a differential expression (DE) analysis is performed comparing hexagons, pixels, or cells assigned to that factor against the rest of the sample to find genes whose expression is most strongly associated with that factor.
What do the columns in the Marker Gene Table represent?
- Gene: Gene symbol.
- FC (Fold Change): How much higher (or lower) the gene's expression is within this factor compared to the rest of the dataset.
- Chi2 / Log10P: Statistical significance of the association (Chi-squared statistic or -log10 of the p-value).
- Count: Total transcript/molecule count for that gene within the factor.
Why do marker genes matter?
- Biological Identity: They help you assign a cell-type or anatomical identity to a factor (e.g., if Factor 7 is enriched for L7/Pcp2, it represents Purkinje cells).
- Cell-Type Specificity: Comparing fold change and significance across genes reveals how specific a factor signature is.
- Pseudobulk Analysis: The DE statistics are computed using the factor's pseudobulk profiles, driving both the Volcano Plot view and the data exports.
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