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• Double click the Spatial report node in the Analyses tab of your project to open a new data viewer session.
• Click Select & Filter , select Criteria, and add the 'Cell type' attribute in the criteria box.
• Select only the Astrocytes  and click  to include only the selected points.
• Now add GFAP to the criteria box and toggle the Pin histogram option.

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• The histogram shows the presence of two distinct populations that segregate based on GFAP expression
• Set the upper threshold as 5, then Classify

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Classify the population

• Classify > Classify selection, name the cells 'A2' and Save
• Now slide the upper threshold to the max and set the lower threshold to 5, then Classify > Classify selection, name the cells 'A1' and Save
• We are now ready to Apply classifications, name the attribute 'Astrocyte sub-population' and Run

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Having classified our sub-populations we can now use that information to identify genes and biologically processes differentially activated between the two.

• Click on the Normalized counts node, select Statistics > Differential analysis > Hurdle model, click Next
• Select the Astrocyte sub-population > Add factors, then click Next
• Drag A1  to the Numerator and A2 to the Denominator box, Add comparison, then click Finish

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Once the differential expression analysis task has completed, you can explore the report and the subsequent analysis steps following this tutorial: Compare expression between cell types with multiple samples

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