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 <https://gabrielodom.github.io/pathwayPCA/index.html>, and the website for the development information is hosted at <https://github.com/gabrielodom/pathwayPCA>.
|Maintainer||Gabriel Odom <[email protected]>|
|Package repository||View on GitHub|
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