adjustRegionMeth: Adjust Methylation Data for Principal Components

In cemordaunt/comethyl: An R Package for Weighted Region Comethylation Network Analysis

Adjust Methylation Data for Principal Components

Description

adjustRegionMeth() adjusts region methylation data for the top principal components, transposes it, and then saves it as a .rds file.

Usage

adjustRegionMeth(
  meth,
  PCs,
  save = TRUE,
  file = "Adjusted_Region_Methylation.rds",
  verbose = TRUE
)

Arguments

meth	A numeric matrix, where each row is a region and each column is a sample. This is typically obtained from getRegionMeth().
PCs	A numeric matrix, where each row is a sample and each column is a principal component. This is typically obtained from getPCs().
save	A logical(1) indicating whether to save the matrix.
file	A character(1) giving the file name (.rds) for the saved matrix.
verbose	A logical(1) indicating whether messages should be printed.

Details

adjustRegionMeth() regresses out the top principal components generated by getPCs(). This is the same approach as taken by sva::sva_network(). More information on the function and approach is given in the documentation and publications related to the sva package.

Value

A numeric matrix, where each row is a sample and each column is a region.

See Also

• getRegionMeth() to extract region methylation values.

• getPCs() to calculate top principal components for region methylation values.

• getMEtraitCor() to compare these top PCs to sample traits.

• getDendro() and plotDendro() to generate and visualize dendrograms.

• getSoftPower() and plotSoftPower() to estimate the best soft-thresholding power and visualize scale-free topology fit and connectivity.

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

Examples

## Not run: 

# Get Methylation Data
meth <- getRegionMeth(regions, bs = bs, file = "Region_Methylation.rds")

# Adjust Methylation Data for PCs
mod <- model.matrix(~1, data = pData(bs))
PCs <- getPCs(meth, mod = mod, file = "Top_Principal_Components.rds")
methAdj <- adjustRegionMeth(meth, PCs = PCs,
                            file = "Adjusted_Region_Methylation.rds")

# Compare Top PCs to Sample Traits
MEtraitCor <- getMEtraitCor(PCs, colData = colData, corType = "bicor",
                            file = "PC_Trait_Correlation_Stats.txt")
PCdendro <- getDendro(PCs, distance = "bicor")
PCtraitDendro <- getCor(PCs, y = colData, corType = "bicor", robustY = FALSE) %>%
        getDendro(transpose = TRUE)
plotMEtraitCor(PCtraitCor, moduleOrder = PCdendro$order,
               traitOrder = PCtraitDendro$order,
               file = "PC_Trait_Correlation_Heatmap.pdf")

# Assess Sample Similarity
getDendro(methAdj, distance = "euclidean") %>%
        plotDendro(file = "Sample_Dendrogram.pdf", expandY = c(0.25,0.08))

# Select Soft Power Threshold
sft <- getSoftPower(methAdj, corType = "pearson", file = "Soft_Power.rds")
plotSoftPower(sft, file = "Soft_Power_Plots.pdf")

# Get Comethylation Modules
modules <- getModules(methAdj, power = sft$powerEstimate, regions = regions,
                      corType = "pearson", file = "Modules.rds")

## End(Not run)

cemordaunt/comethyl documentation built on Oct. 20, 2023, 5:47 p.m.