Principal component analysis plot

This will create a principal component plot as shown in figure 27.82.

Image pca_plot
Figure 27.82: A principal component analysis colored by group.

The plot shows the projection of the samples onto the two-dimensional space spanned by the first and second principal component. (These are the orthogonal directions in which the data exhibits the largest and second-largest variability).

The plot in figure 27.82 is based on a two-group experiment. The group relationships are indicated by color. We expect the samples from within a group to exhibit less variability when compared, than samples from different groups. Thus samples should cluster according to groups and this is what we see. The PCA plot is thus helpful in identifying outlying samples and samples that have been wrongly assigned to a group.

In the Side Panel to the left, there is a number of options to adjust the view. Under Graph preferences, you can adjust the general properties of the plot.

Below the general preferences, you find the Dot properties:

Note that if you wish to use the same settings next time you open a principal component plot, you need to save the settings of the Side Panel.