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An advantage of UMAP over t-SNE is that is preserves more of the global structure of the data. This means that with UMAP, more similar clusters are closer together while dissimilar clusters are further apart. With t-SNE, the relative positions of clusters to each other are often uninformative.  

• Click the 2D radio button forfor Plot style to switch to the 2D UMAP (Figure 20)
  
  

• Click Image Added to activate the lasso tool
• Draw a lasso around clusters 3, 4, and 6 (Figure 21) to select them
  
  

• Click Image Added to filter to include only the selected cells
• Click Image Added to rescale the axes to the included cells (Figure 22)
  
  

Because we merged the gene and protein expression data, we can visualize a mix of genes and proteins on the gene expression UMAP.

• Choose Expression from the Color by drop-down menu
• Type NKG7 in the search box and choose NKG7 from the drop-down (Figure 23)
  
  

• Click Image Added to color by a second feature (gene or protein)
• Type CD4 and choose CD4_TotalSeqB from the drop-down (Figure 24)
  
  

This will color the plot by NKG7 gene expression and CD4 protein expression, a marker for helper T cells. We can add a third feature.

• Click Image Added to color by a second feature (gene or protein)
• Type CD3 and choose CD3_TotalSeqB from the drop-down

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 and the mix of green, red, and blue 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 25). CD3 is a pan-T cells marker, which helps confirm that this group of clusters is composed of T cells. 

In addition to coloring by the expression of genes and proteins, we can select cells by their expression levels.

• Click the Features tab in the Selection / Filtering section of the control panel
• Type NKG7 in the ID search bar of the Features tab
• Click NKG7 to select it
• Click Image Added to add a filter for NKG7 expression

By default, any cell that expresses >= 1 normalized count of NKG7 is now selected (Figure 26).

• Type CD3 in the ID search bar of the Features tab
• Click CD3_TotalSeqB from the drop-down
• Click Image Added to add a filter for CD3 protein expression

Now, any cell that expresses >= 1 normalized count for NKG7 gene and CD3 protein is selected. You can also require that a cell not express a gene or protein.

• Type CD4 in the ID search bar of the Features tab
• Click CD4_TotalSeqB from the drop-down
• Click Image Added to add a filter for CD4 protein expression
• Set the CD4_TotalSeqB filter to <= 2 

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 27).

We can classify these cells. Because they express the pan T cell maker, CD3, and the cytotoxic marker, NKG7, but not the helper T cell marker, CD4, we can classify these cells as Cytotoxic T cells. 

• Click Classify selection
• Type Cytotoxic T cells for the name
• Click Save

To classify the helper T-cells, we can modify the selection criteria. 

• Set NKG7 to =< 1
• Set CD4_TotalSeqB to >= 2

We have now selected the CD4 positive, CD3 positive, NKG7 negative helper T cells (Figure 28).

• Click Classify selection
• Type Helper T cells for the name
• Click Save

We can check the results of our classification.

• Click Clear selection
• Select Classification from the Color by drop-down menu (Figure 29)

To return to the full data set, we can clear the filter.

• Click Clear filters 

The zoom level will also be reset.