corPs {rOCEAN} | R Documentation |
Calculates pairwise matrix of p-values based on Pearson's correlation test for two matrices. To gain speed and manage RAM usage, the matrices are split into several smaller chunks.
corPs(pm1, pm2, type = c("Mat", "Vec"), pthresh = 0.05)
pm1 , pm2 |
Subsets of two omics data sets where rows are the features and columns are samples. The rows of the two matrices would define the two-way feature set of interest. |
type |
Two options are available. Mat: Calculate the correlation of subsets and return a matrix; Vec: calculate the correlation matrix, subset by the given threshold and return a vector of p-values. |
pthresh |
Only relevant for type="Vec". The threshold by which the p-values are filtered (p>pthresh is removed). Default value is 0.05. |
Either a matrix or vector of pairwise p-values, as indicated by type
parameter.
#number of subjects
n<-30
#number of features from omic1 in pathway
n_rows<-20
#number of features from omic2 in pathway
n_cols<-30
#random datasets
set.seed(1258)
pm1<-matrix(runif(n_rows*n, min=0, max=1)^8, nrow=n_rows, ncol=n)
pm2<-matrix(runif(n_rows*n, min=0, max=1)^8, nrow=n_rows, ncol=n)
#calculate correlation matrix
pmat<-corPs(pm1, pm2, type="Mat")
pmat