Now that we have clustered our data we can start the process of identifying the cell populations present in our tissue. To start we can analyse Using the results of our dimension reduction analysis, by looking we will look at the clustering results on the UMAP and the spatial map:

• Double click the Spatial report node. This will automatically open a new dataviewer Data viewer session and plot the spatial map with the high resolution image in the background.
• Click on New plot > 3D Scatter plot and select the UMAP node.

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• Click on New plot > Table and select the Biomarkers table generated after the Graph-based clustering task.
• Click anywhere on the Spatial plot, then click Style, click on the node selector next to the Color by dropbox, select the Graph-based clustering node

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• Now select 'Graph based' from the options. Click on the legend title, drag and drop it on the color option on the UMAP plot:

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Now that we have plotted the clustering results we can start inspecting them. We have identified markers for 13 clusters, with apparent spatial separation. The sample is human front cortex, thus we can expect our clusters to represent some of the major cell types found in the tissue (eg. astrocytes, microglia, oligodendrocytes etc). Looking at the markers for Cluster 4, we can see there are a few known astrocyte markers: AQP4, AGT, FGFR3.

• Drag and drop each one of the 3 genes from the biomarkers table onto of the 'Green, Red, Blue' features of the spatial plot to visualise the in-tissue expression:

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• Zoom in to better observe the cell-level expression patters:

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• Let's classify the cells from cluster 4 as astrocytes:
  • Click Select & Filter > Criteria, drag the Graph-based attribute on the Add criteria box and select only Cluster 4.
  • Click Classify > Classify selection. Type 'Astrocytes' and Save. 
  • Click Apply classifications, type 'Cell type' in the box and click Run.

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