# Classify subpopulations & differential expression analysis

### Identification of A1/A2 Astrocytes <a href="#classifysubpopulations-and-differentialexpressionanalysis-identificationofa1-a2astrocytes" id="classifysubpopulations-and-differentialexpressionanalysis-identificationofa1-a2astrocytes"></a>

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 ![](https://documentation.partek.com/download/thumbnails/98206089/Screenshot%202024-07-19%20at%2010.47.50.png?version=1\&modificationDate=1721382473109\&api=v2) 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

<figure><img src="/files/wISuWD1YuwrRbvRJnoon" alt=""><figcaption></figcaption></figure>

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**

<figure><img src="/files/5sE8XJfjGDR4NFILlZkk" alt=""><figcaption></figcaption></figure>

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**

<figure><img src="/files/CnC4SsK8FBM8rnABsPKQ" alt=""><figcaption></figcaption></figure>

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](/partek/partek-flow/tutorials/single-cell-rna-seq-analysis-multiple-samples/compare-expression-between-cell-types-with-multiple-samples.md)

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### Additional Assistance <a href="#classifysubpopulations-and-differentialexpressionanalysis-additionalassistance" id="classifysubpopulations-and-differentialexpressionanalysis-additionalassistance"></a>

If you need additional assistance, please visit [our support page](http://www.partek.com/support) to submit a help ticket or find phone numbers for regional support.


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