Performing PCA for a Dataset

Overview

GeneLinker™ has the facility to perform Principal Components Analysis (PCA) on a dataset. For a complete description of PCA,  see Overview of Principal Components Analysis.

Actions

1. Click a complete dataset in the Experiments navigator. The item is highlighted.

2. Click the Principal Component Analysis toolbar icon , or select Principal Component Analysis from the PCA menu, or right-click the item and select Principal Component Analysis from the shortcut menu. The PCA parameters dialog is displayed.

3. Select whether to perform PC calculation on either Genes or Samples.

4. Click OK. The Experiment Progress dialog is displayed. It is dynamically updated as the PCA operation is performed.

Upon successful completion, a new Gene or Sample Principal Components Analysis item is added under the original item in the Experiments navigator.

Plotting PCA Results

1. Click a Gene or Sample Principal Component Analysis item in the Experiments navigator. The item is highlighted.

2. Select a plot type from the PCA menu. For a complete description of the plot, please see:

•  Scree Plot  

•  Loadings Line Plot  

•  Loadings Scatter Plot  

•  Loadings Color Matrix Plot  

•  Score Plot  

•  3D Score Plot  

Related Topics:

Overview of Principal Component Analysis (PCA) Functionality

Tutorial 5: Principal Component Analysis (PCA)