Nothing
#' @title Calculate a correlation matrix.
#' @description This function takes one or two input matrices and calculates a correlation matrix from it using the speed-optimized correlation function from WGCNA.
#' @param matA Input data matrix with numeric entries.
#' @param corrType The type of correlation to be performed. Either "pearson" or "spearman".
#' @param matB Optional input data matrix with which the comparison with matA will be made.
#' @param secondMat Logical indicator of whether there is a second matrix in the comparison or not.
#' @param use The "use" method for performing the correlation calculation. See ?cor for more information. Default = "pairwise.complete.obs" (which is one of the speed-optimized versions; see ?WGCNA::cor for more).
#' @return A correlation matrix.
#' data(darmanis); darmanis_subset = darmanis[1:30, ]
#' matcor_res = matCorr(matA = darmanis_subset, corrType = "pearson")
#' @export
matCorr <- function(matA, corrType, use = "pairwise.complete.obs", matB = NULL, secondMat = FALSE){
if(!secondMat){
if(corrType %in% "pearson"){
corrs = WGCNA::cor(matA, use = use)
}
if(corrType %in% "spearman"){
corrs = WGCNA::cor(matA, use = use, method = "spearman")
}
}
if(secondMat){
if(corrType %in% "pearson"){
corrs = WGCNA::cor(matA, matB, use = use)
}
if(corrType %in% "spearman"){
corrs = WGCNA::cor(matA, matB, use = use,
method = "spearman")
}
}
return(corrs)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.