Calculate clock correlation distance (CCD).Source:
Quantify the similarity of gene co-expression between a reference and a test dataset. Statistical significance is calculated using permutation of the genes.
groupVec = NULL,
refEmat = NULL,
nPerm = 1000,
geneNames = NULL,
dopar = FALSE,
scale = FALSE
Correlation matrix to be used as the reference, such as comes from
getRefCor(). Should contain Spearman correlation values.
Matrix of expression values, where each row corresponds to a gene and each column corresponds to a sample. The rownames and colnames of
refCorshould be present in the rownames of
emat. For the p-value calculation, it is important that
ematinclude all measured genes, not just those in
Optional vector indicating the group to which group each sample belongs. If not provided, the function assumes all samples belong to the same group.
Optional expression matrix for calculating co-expression for the reference, with the same organization as
emat. Only used if
refCoris not provided.
Number of permutations for assessing statistical significance.
Optional vector indicating a subset of genes in
refEmatto use for calculating the CCD.
Logical indicating whether to process features in parallel. Make sure to register a parallel backend first.
Logical indicating whether to scale CCD by the number of gene pairs.