Mark CpGs in contiguous and co-methylated region

MarkComethylatedCpGs(
  betaCluster_mat,
  betaToM = TRUE,
  epsilon = 1e-08,
  rDropThresh_num = 0.4,
  method = c("pearson", "spearman"),
  use = "complete.obs"
)

Arguments

betaCluster_mat: matrix of beta values, with rownames = sample ids and column names = CpG ids. Note that the CpGs need to be ordered by their genomic positions, this can be accomplished by the OrderCpGbyLocation function.
betaToM: indicates if beta values should be converted to M values before computing correlations. Defaults to TRUE.
epsilon: When transforming beta values to M values, what should be done to values exactly equal to 0 or 1? The M value transformation would yield -Inf or Inf which causes issues in the statistical model. We thus replace all values exactly equal to 0 with 0 + epsilon, and we replace all values exactly equal to 1 with 1 - epsilon. Defaults to epsilon = 1e-08.
rDropThresh_num: threshold for minimum correlation between a cpg with the rest of the CpGs. Defaults to 0.4.
method: correlation method; can be "pearson" or "spearman"
use: method for handling missing values when calculating the correlation. Defaults to "complete.obs" because the option "pairwise.complete.obs" only works for Pearson correlation.

Value

A data frame with the following columns:

CpG : CpG ID
keep : The CpGs with keep = 1 belong to the contiguous and co-methylated region
ind : Index for the CpGs
r_drop : The correlation between each CpG with the sum of the rest of the CpGs

Details

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.

Examples

   data(betaMatrix_ex1)
   
   MarkComethylatedCpGs(
     betaCluster_mat = betaMatrix_ex1,
     betaToM = FALSE,
     method = "pearson"
   )
#>          CpG keep ind    r_drop
#> 1 cg10170214    1   1 0.7359922
#> 2 cg06518233    1   2 0.8936653
#> 3 cg18326783    1   3 0.8901418
#> 4 cg05229649    0   4 0.1862278