Apply the Supervised PCA and Adaptive, Elastic-Net, Sparse PCA
methods to extract principal components from each pathway. Use these pathway-
specific principal components as the design matrix relating the response to
each pathway. Return the model fit statistic p-values, and adjust these values
for False Discovery Rate. Return a data frame of the pathways sorted by their
adjusted p-values. This package has corresponding vignettes hosted in the
``User Guides'' page of
|Maintainer||Gabriel Odom <[email protected]>|
|Package repository||View on GitHub|
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