Statistics / PCA

Description

Calculates principal components for the selected sample list and saves them for further use.

Parameters

• Data to use for the analysis (chips) [chips]
• Variability to explain (0...100) [80]
• Should data be scaled (yes,no) [no]
• Should data be centered (yes, no) [yes]

Details

A principal component analysis is run for samples. Principal components are retained until the explained variability exceeds the specified value. The output of the analysis can be visualized using the 3D scatterplot in the visualization panel. To do this, select the pca.tsv spreadhseet and change the visualization method to 3D scatterplot for PCA

Output

A sample list with principal components (those are not expression values) and another table indicating the proportion of variance explained by each component.