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• Click the 2D radio button for Plot style to switch to the 2D UMAP (Figure 4243)
  
  

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• Click  to activate the lasso tool
• Draw a lasso around clusters 3, 4, and 6 (Figure 4344) to select them
  
  

• Click  to filter to include only the selected cells
• Click  to rescale the axes to the included cells (Figure 4445)
  
  

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• Choose Expression from the Color by drop-down menu
• Type NKG7 in the search box and choose NKG7 from the drop-down (Figure 4546)
  
  

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• Click  to color by a second feature (gene or protein)
• Type CD4 and choose CD4_TotalSeqB from the drop-down (Figure 4647)
  
  

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This will color the plot by NKG7 gene expression, CD4 protein expression, and CD3 protein expression. Each feature gets a color channel, green, red, or blue. Cells without expression are black. The mix of green, red, and blue coloring each cell is determined by the relative expression of the three genes. Cells expressing both CD4 protein (red) and CD3 protein (blue), but not NKG7 (green) are purple, while cells expressing both NKG7 (green) and CD3 protein (blue) are teal (Figure 4748). CD3 is a pan-T cells marker, which indicates that this group of clusters is composed of T cells. 

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By default, any cell that expresses >= 1 normalized count of NKG7 is now selected (Figure 4849).

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We have now selected only cells that express >= 1 normalized count for NKG7 gene and CD3 protein, but also have <= 2 normalized count for CD4 protein (Figure 4950).

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We have now selected the CD4 positive, CD3 positive, NKG7 negative helper T cells (Figure 5051).

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• Click Clear selection
• Select Classifications from the Color by drop-down menu (Figure 5152)
  
  

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The zoom level will also be reset (Figure 5253).

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 There are several clusters that show high levels of CD19 protein expression (Figure 5354). We can filter to these cells to examine them more closely.

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• Click  to activate the lasso tool
• Draw a lasso around the CD19 protein-expressing clusters to select them
• Click  to filter to include only the selected cells
• Click  to rescale the axes to the included cells (Figure 5455)
  
  

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• Choose Graph-based from the Color by drop-down menu (Figure 5556)

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• Choose Graph-based from the Select by drop-down in the Attributes tab of the Selection / Filtering section of the control panel 
• Click the check box for 7 to select cluster 7
• Click Classify selection (Figure 5657)
  
  

• Name the cells Doublets
• Click Save 
• Click Clear selection Click  to filter to exclude the selected cells

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This will color the plot by IGHD and IGHA1 (Figure 5758).

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• Select the left-hand cluster with IGHA1 expression (Figure 5859)
  
  

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• Draw a lasso around the right-hand cluster (Figure 5960)
  
  

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• Select Classifications from the Color by drop-down menu
• Click Clear filters to view all cells (Figure 6061)
  
  

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• Click the Classified groups data node
• Click Filtering 
• Click Filter groups
• Set to exclude Classifications is Doublets using the drop-down menus
• Click AND
• Set the second filter to exclude Classifications is N/A using the drop-down menus 
• Click Finish to apply the filter (Figure 6162)
  
  

This produces a Filtered groups counts data node (Figure 6263).

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This will produce two data nodes, one for each data type (Figure 6364).

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• Click Finish to run the statistical test (Figure 6465)
  
  

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The report lists each feature tested, giving p-value, false discovery rate adjusted p-value (FDR step up), and fold change values for each comparison (Figure 6566).

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This opens a violin plot showing CD25 expression for cells in each of the classifications (Figure 6667).

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• Click the Feature list data node
• Click Exploratory analysis in the toolbox
• Click Hierarchical clustering 
• Click Finish to run with default settings
• Double-click the Hierarchical clustering task node to open the heat map (Figure 6768)
  
  

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This generates a customized heat map to illustrate how the cell types differ in their protein expression (Figure 6869).

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• Double-click the GSA task node to open the task report (Figure 6970)
  
  

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Each gene is shown as a point on the plot with cut-off lines for fold change and p-value or FDR step up set using the control panel on the left (Figure 7071). The number of genes up and down regulated according to the cut-offs is listed at the bottom of the plot. Mousing over a point shows the gene name and other information. 

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The number at the top of the filter will update to show the number of included genes (Figure 7172).

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The pathway enrichment results list KEGG pathways, giving an enrichment score and p-value for each (Figure 7273).

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The KEGG pathway map shows up-regulated genes from the input list in red and down-regulated genes from the input list in green (Figure 73734). 

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