Computes leave-one-out correlations (rDrop) for each CpG
CreateRdrop(data, method = c("pearson", "spearman"), use = "complete.obs")a dataframe with rownames = sample IDs, column names = CpG IDs.
method for computing correlation, can be "pearson" or
"spearman", and is passed to the cor function.
method for handling missing values when calculating the
correlation. Defaults to "complete.obs" because the option
"pairwise.complete.obs" only works for Pearson correlation.
A data frame with the following columns:
CpG : CpG ID
r_drop : The correlation between each CpG with the sum of
the rest of the CpGs
An outlier CpG in a genomic region will typically have low
correlation with the rest of the CpGs in a genomic region. On the other
hand, in a cluster of co-methylated CpGs, we expect each CpG to have high
correlation with the rest of the CpGs. The r.drop statistic is used
to identify these co-methylated CpGs here.
data(betaMatrix_ex1)
CreateRdrop(data = betaMatrix_ex1, method = "pearson")
#> CpG r_drop
#> 1 cg10170214 0.7359922
#> 2 cg06518233 0.8936653
#> 3 cg18326783 0.8901418
#> 4 cg05229649 0.1862278