PermTestReg.Rd
Given an OmicsReg
object and a list of pathway PCs from
the ExtractAESPCs
function, test if each pathway with
features recorded in the bioassay design matrix is significantly related
to the continuous response.
PermTestReg( OmicsReg, pathwayPCs_ls, numReps = 0L, parallel = FALSE, numCores = NULL, ... ) # S4 method for OmicsReg PermTestReg( OmicsReg, pathwayPCs_ls, numReps = 0L, parallel = FALSE, numCores = NULL, ... )
OmicsReg  A data object of class 

pathwayPCs_ls  A list of pathway PC matrices returned by the

numReps  How many permutations to estimate the \(p\)value? Defaults
to 0 (that is, to estimate the \(p\)value parametrically). If

parallel  Should the computation be completed in parallel? Defaults to

numCores  If 
...  Dots for additional internal arguments (currently unused). 
A named vector of pathway permutation \(p\)values.
This function takes in a list of the first principal components
from each pathway and an object of class OmicsReg
. This function
will then calculate the AIC of a multivariate linear model (via the
lm
function) with the original observations as
response and the pathway principal components as the predictor matrix. Note
that the AIC and loglikelihood are proportional because the number of
parameters in each pathway is constant.
Then, this function will create numReps
permutations of the
regression response, fit models to each of these permuted responses
(holding the path predictor matrix fixed), and calculate the AIC of each
model. This function will return a named vector of permutation
\(p\)values, where the value for each pathway is the proportion of
models for which the AIC of the permuted response model is less than the
AIC of the original model.
# DO NOT CALL THIS FUNCTION DIRECTLY. # Use AESPCA_pVals() instead if (FALSE) { ### Load the Example Data ### data("colonSurv_df") data("colon_pathwayCollection") ### Create an OmicsSurv Object ### colon_Omics < CreateOmics( assayData_df = colonSurv_df[, (2:3)], pathwayCollection_ls = colon_pathwayCollection, response = colonSurv_df[, 1:2], respType = "reg" ) ### Extract Pathway PCs and Loadings ### colonPCs_ls < ExtractAESPCs( object = colon_Omics, parallel = TRUE, numCores = 2 ) ### Pathway pValues ### PermTestReg( OmicsReg = colon_Omics, pathwayPCs_ls = colonPCs_ls$PCs, parallel = TRUE, numCores = 2 ) }