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Because we have classified our cells, we can now filter based on those classifications. This can be used to focus on a single cell type for re-clustering and sub-classification or to exclude cells that are not of interest for downstream analysis.

• Click the Classified result Merged counts data node
• Click Filtering 
• Click Filter groupscells
• Set to exclude Cell type is Doublets using the drop-down menus
• Click ANDOR
• Set the second filter to exclude Cell type is N/A using the drop-down menus 
• Click Finish to apply the filter (Figure 1)

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This produces a Filtered counts data node (Figure 2).

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Re-split the Matrix

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Differential Analysis and Visualization - Protein Data

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• Click the Antibody Capture data node
• Click Statistics
• Click Differential analysis 
  
• Click GSAANOVA then click Next

The first step is to choose which attributes we want to consider in the statistical test. 

• Check Click Cell type to include it in the statistical test
• Click Add factor
• Click Next 

Next, we will set up the comparison we want to make. Here, we will compare the Activated and Mature B cells.

• Check Drag Activated B cells in the top panel
• Check Drag Mature B cells in the bottom panel 
• Click Add comparison

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The GSA ANOVA task produces a GSA an ANOVA data node.

• Double-click the GSA ANOVA data node to open the task report

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In addition to the listed information, we can access dot and violin plots for each gene or protein from this table.

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This opens a dot plot in a new data viewer session, showing CD45A expression for cells in each of the classifications (Figure 6). First, we exclude Doublets and N/A cells from the plot:

• Open Select and filter, select Criteria
• Drag "Cell type" from the legend title to the Add criteria box
• Uncheck Doublets and N/A
• Click to include selected points

We can use the Configuration panel on the left to edit this plot.

• Open the Style icon
• Switch on Violins under Summary 
• Switch on Overlay under Summary
• Switch on Colored under Summary
• Select the Graph-based clustering node in the Color by section
• Color by Graph-based clusters under Color and use the slider to decrease the Opacity 
• Open the Axes icon
• Select the Graph-based clustering node in the X axis section
• Change the X axis data to Graph-based clusters 
• Use the slider to increase the Jitter on the X axis (Figure 7)

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• Click the project name to return to the Analyses tab

To visualize all of the proteins at the same time, we can make a hierarchical clustering heat map.

• Click the GSA ANOVA data node
• Click Exploratory analysis in the toolbox
• Click Hierarchical clustering/heatmap
• In the Ordering the Cell order section, choose Graph-based clusters from the Cell Assign order drop-down list
• Click Finish to run with the other default settings
• Double-click the Hierarchical clustering task node to open the heatmap

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• Activate the Transpose switch which will switch the Row and Column labels, so now the Row labels will be shown (Figure 9)

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• Open the Dendrograms icon
• Choose Row color By cluster and change Row clusters to 4
• Change Row dendrogram size to 80 (Figure 10)

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• In the Heatmap icon
• Navigate to Range under Color
• Set the Min and Max to -1.2 and 1.2, respectively
• Change the Shape to Circle (Figure 11)

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• Switch the Shape back to Rectangle 
• Change the Color Palette by clicking on the color squares and selecting colors from the rainbow. Click outside of the selection box to exit this selection. The color options can be dragged alone the Palette to highlight value differences (Figure 12). 

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Feel free to explore the other tool options on the left to customize the plot further.

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• Click the project name to return to the Analyses tab
• Click the Gene Expression data node
• Click the Antibody Capture data node
• Click Statistics
• Click Differential analysis 
  
• Click GSA
• Check Cell type to include it in the statistical test
• ANOVA then click Next
• Click Cell type 
• Click Add factor
• Click Next 
• Check Drag Activated B cells in the top panel
• Check Drag Mature B cells in the bottom panel 
• Click Add comparison Click comparison

The comparison should appear in the table as Activated B cells vs. Mature B cells.

• Click Finish to run the statistical test

As before, this will generate a GSA an ANOVA task node and a GSA n ANOVA data node.

• Double-click the GSA ANOVA task node to open the task report (Figure 13)

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Because more than 20,000 genes have been analyzed, it is useful to use a volcano plot to get an idea about the overall changes.

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• Click the GSA ANOVA report tab in your web browser to return to the full report

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• Click Image RemovedImage Added to create a new data node including only these significantly different genes

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To get a better idea about the changes in each enriched pathway, we can view an interactive KEGG pathway map.

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