Calculate Module Preservation

getModulePreservation() examines module replication between a reference and a test data set by estimating various preservation statistics, which are then saved as a .txt file. Correlations are performed using either pearson or bicor methods.

Usage

getModulePreservation(
  meth_disc,
  regions_disc,
  meth_rep,
  regions_rep,
  corType = c("pearson", "bicor"),
  maxPOutliers = 0.1,
  nPermutations = 100,
  save = TRUE,
  file = "Module_Preservation_Stats.txt",
  verbose = TRUE
)

Arguments

meth_disc

A numeric matrix, where each row is a sample and each column is a region. This is typically obtained from adjustRegionMeth() and is related to the discovery (reference) data set.

regions_disc

A data.frame of regions with module assignments, which is typically obtained from getModules() and is related to the discovery data set.

meth_rep

A numeric matrix, where each row is a sample and each column is a region. This is typically obtained from adjustRegionMeth() and is related to the replication (test) data set.

regions_rep

A data.frame of regions with module assignments, which is typically obtained from getModules() and is related to the replication data set.

corType

A character(1) indicating which correlation statistic to use in the adjacency calculation.

maxPOutliers

A numeric(1) specifying the maximum percentile that can be considered outliers on each side of the median for the bicor statistic.

nPermutations

A numeric(1) indicating the number of permutations to perform in the permutation test.

save

A logical(1) indicating whether to save the data.frame.

file

A character(1) giving the file name (.txt) for the saved data.frame.

verbose

A logical(1) indicating whether messages should be printed.

Value

A data.frame giving preservation statistics for each module in the discovery data set.

Details

Identical sets of regions should be assessed and assigned modules within discovery (reference) and replication (test) data sets, though the replication regions may be a subset of the discovery regions due to low coverage. It's also recommended to filter CpGs so identical loci are also assessed within regions. Network parameters should be as similar as possible, although modules should be identified independently between the discovery and replication datasets. Preservation statistics are calculated by WGCNA::modulePreservation(), with corFnc set to either cor or bicor. More information is given in the documentation for WGCNA::modulePreservation().

See also

• getModules() to build a comethylation network and identify modules of comethylated regions.

• plotModulePreservation() to visualize module preservation statistics.

Examples

if (FALSE) {
# Calculate Module Preservation
regions_disc <- modules_disc$regions
regions_rep <- modules_rep$regions
preservation <- getModulePreservation(methAdj_disc,
                                      regions_disc = regions_disc,
                                      meth_rep = methAdj_rep,
                                      regions_rep = regions_rep,
                                      corType = "pearson",
                                      file = "Module_Preservation_Stats.txt")

# Visualize Module Preservation
plotModulePreservation(preservation, file = "Module_Preservation_Plots.pdf")
}