calculate_cvm_gene {EMDomics} | R Documentation |
Calculate CVM score for a single gene
calculate_cvm_gene(vec, outcomes, sample_names)
vec |
A named vector containing data (e.g. expression data) for a single gene. |
outcomes |
A vector of group labels for the samples. The names must correspond
to the names of |
sample_names |
A character vector with the names of the samples in |
All possible combinations of the classes are used as pairwise comparisons.
The data in vec
is divided based on class labels based on the outcomes
identifiers given. For each pairwise computation, the hist
function is
used to generate histograms for the two groups. The densities are then retrieved
and passed to CramerVonMisesTwoSamples
to compute the pairwise CVM score. The
total CVM score for the given data is the average of the pairwise CVM scores.
The cvm score is returned.
# 100 genes, 100 samples dat <- matrix(rnorm(10000), nrow=100, ncol=100) rownames(dat) <- paste("gene", 1:100, sep="") colnames(dat) <- paste("sample", 1:100, sep="") # "A": first 50 samples; "B": next 30 samples; "C": final 20 samples outcomes <- c(rep("A",50), rep("B",30), rep("C",20)) names(outcomes) <- colnames(dat) calculate_cvm_gene(dat[1,], outcomes, colnames(dat))