Principal component analysis plot (2D)

The default view is a two-dimensional principal component plot as shown in figure 26.23.

Image pca_plot
Figure 26.23: A principal component plot.

The plot shows the projection of the samples onto the two-dimensional space spanned by the first and second principal components of the covariance matrix. The expression levels used as input are normalized log CPM values, see TMM Normalization.

The view settings can be adjusted using the Side Panel. Under Graph preferences, you can adjust the general properties of the plot.

Below the general preferences, you find the Dot properties:

Note that the Dot properties may be overridden when the Metadata options are used to control the visual appearance (see below).

The Principal Components group determines which two principal components are used in the 2D plot. By default, the first principal component is shown for the X axis and the second principal component is shown for the Y axis. The value after the principal component identifier (for example "PC1 (72.5 %)") displays the amount of variance explained by this particular principal component.

The Metadata group allows metadata associated with the Expression tracks to be visualized in a number of ways:

The graph and axes titles can be edited simply by clicking them with the mouse. These changes will be saved when you Save (Image Save_Blue_16_n_p) the graph - whereas the changes in the Side Panel need to be saved explicitly (see Saving, removing and applying saved settings).