# Classify subpopulations & differential expression analysis
### Identification of A1/A2 Astrocytes
Astrocytes populations are often found in two activation states: the neurotoxic or pro-inflammatory phenotype (A1) and the neuroprotective or anti-inflammatory phenotype (A2). Now that we have identified our astrocyte population we can move onto the sub-classification of A1/A2 astrocytes. For this we are going to use the GFAP marker, a commonly used marker for A1 astrocytes.
* 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
* The histogram shows the presence of two distinct populations that segregate based on *GFAP* expression
* Set the upper threshold as 5
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**
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**
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](https://help.connected.illumina.com/partek/partek-flow/tutorials/single-cell-rna-seq-analysis-multiple-samples/compare-expression-between-cell-types-with-multiple-samples)
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