getPathPCLs {pathwayPCA} | R Documentation |
superpcOut
- or aespcOut
-class
Object.Given an object of class aespcOut
or superpcOut
,
as returned by the functions AESPCA_pVals
or
SuperPCA_pVals
, respectively, and the name or unique ID of
a pathway, return a data frame of the principal components and a data
frame of the loading vectors corresponding to that pathway.
getPathPCLs(pcOut, pathway_char, ...) ## S3 method for class 'superpcOut' getPathPCLs(pcOut, pathway_char, ...) ## S3 method for class 'aespcOut' getPathPCLs(pcOut, pathway_char, ...)
pcOut |
An object of classes |
pathway_char |
A character string of the name or unique identifier of a pathway |
... |
Dots for additional arguments (currently unused). |
Match the supplied pathway character string to either the
pathways
or terms
columns of the pVals_df
data frame
within the pcOut
object. Then, subset the loadings_ls
and
PCs_ls
lists for their entries which match the supplied pathway.
Finally, return a list of the PCs, loadings, and the pathway ID and name.
A list of four elements:
PCs
: A data frame of the principal components
Loadings
: A matrix of the loading vectors with features
in the row names
pathway
: The unique pathway identifier for the
pcOut
object
term
: The name of the pathway
NULL
NULL
### Load Data ### data("colonSurv_df") data("colon_pathwayCollection") ### Create -Omics Container ### colon_Omics <- CreateOmics( assayData_df = colonSurv_df[, -(2:3)], pathwayCollection_ls = colon_pathwayCollection, response = colonSurv_df[, 1:3], respType = "survival" ) ### Calculate Supervised PCA Pathway p-Values ### colon_superpc <- SuperPCA_pVals( colon_Omics, numPCs = 2, parallel = TRUE, numCores = 2, adjustment = "BH" ) ### Extract PCs and Loadings ### getPathPCLs( colon_superpc, "KEGG_PENTOSE_PHOSPHATE_PATHWAY" )