selectCommonComps: Select common components in two data blocks
Description
This function applies a Simultaneous Component Analysis (SCA). The idea is that the scores for both blocks should have a similar behaviour if the components are in the common mode. Evaluation is by the ratios between the explained variances (SSQ) of each block and the estimator. The highest component count with 0.8 < ratio < 1.5 is selected.
Usage
selectCommonComps(X, Y, Rmax)
Arguments
X
Matrix of omics data
Y
Matrix of omics data
Rmax
Maximum number of common components to find
Value
A list with components:
common
Optimal number of common components
ssqs
Matrix of SSQ for each block and estimator
pssq
ggplot object showing SSQ for each block and estimator
pratios
ggplot object showing SSQ ratios between each block and estimator