the principal components analysis (PCA) scatter plot allows us to visualize similarities and differences between the samples in a data set. 

• Select the Gene Counts data node 
• Select Visualizations from the task menu
• Select PCA from the Visualizations section of the task menu
• Select Finish to run PCA with the default options

The PCA task node will be added to the pipeline (Figure)

• Double click the PCA task node to open the PCA scatter plot (Figure)

The scatter plot shows each sample as a point in a three dimensional plot. The x, y, and z axes are the first three principal components. The percentage of total variance explained by each is listed next to the axis label. The size of each axis is determined by the variance along that axis. The plot is fully interactive; it can be rotated and points selected. 

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