The function computes a Matthews correlation coefficient for two factors
provided to the function. It assumes each factor is a factor of class labels,
and the enteries are paired in order of the vectors.
Usage
mcc(x, y, nperm = 1000, nthread = 1)
Arguments
- x, y
factor of the same length with the same number of levels
- nperm
numeric number of permutations for significance
estimation. If 0, no permutation testing is done
- nthread
numeric can parallelize permutation texting using
BiocParallels bplapply
Value
A list with the MCC as the $estimate, and p value as $p.value
Details
Please note: we recommend you call set.seed() before using this function to
ensure the reproducibility of your results. Write down the seed number or
save it in a script if you intend to use the results in a publication.
Examples
x <- factor(c(1,2,1,2,3,1))
y <- factor(c(2,1,1,1,2,2))
mcc(x,y)
#> Warning: The number of levels x and y was different. Taking the union of all class labels.
#> $estimate
#> [1] -0.452267
#>
#> $p.value
#> [1] 0.348
#>