MPEA.r contains the following 2 functions

MPEA: Simple Multivariate pathway enrichment Analysis. Arguments:

1. expressions: A matrix of expression values. The samples are rows and the columns are the expression values of individual genes ( or similar). The column names should be the name of the genes as are in the pathway. 2.pathway: a list of individual pathways to be analyzed. Each element of the list consists of a string of the names of the genes inside the pathway
2. y: Vector of phenotypes. For dichotomous cases a binary vector would be satisfactory.
3. num_simulation: The number of simulation runs for p-value estimation.
4. ncore: number of CPU cores used for the computation
5. seed.number: set for result reproduction.

Value: A vector containing the unadjusted p-value of individual pathways submitted to the code.

MPEA_subsampling: Multivariate pathway enrichment Analysis with windowing compensation. Arguments:

1. Expressions: A matrix of expression values. The samples are rows and the columns are the expression values of individual genes (or similar). The column names should be the name of the genes as are in the pathway.
2. pathway: a list of individual pathways to be analyzed. Each element of the list consists of a string of the names of the genes inside the pathway
3. y: Vector of phenotypes. For dichotomous cases, a binary vector would be satisfactory.
4. subsampling_size: The size of the sampling window
5. numsim1: The number of windowing simulation runs on the pathway
6. numsim2: The number of simulation runs on the array.
7. ncore: number of CPU cores used for the computation
8. dcor_test_repetition: Passed as R ( repitition count to dcor.test)
9. sim_mode: the flag choosing between average ( "mean") and maximum ("max") dcor values for significance analysis. Value: A list containnig:
10. pathway_dcor: Pathway distance correlation.
11. pathway_dcor_test: The result of energy::dcor.test on the pathway 3.simulated_p_value: The estimated p_value of individual pathways. =======