Visualize a Module Eigennode - Trait Correlation as a Dot Plot

plotMEtraitDot() takes a vector of module eigennode values and a vector of categorical sample trait values, generates a dot plot, and then saves it as a .pdf. ME and trait must be in the same order.

Usage

plotMEtraitDot(
  ME,
  trait,
  traitCode = NULL,
  colors = NULL,
  fun.data = c("median_hilow", "mean_cl_boot", "mean_cl_normal", "mean_sdl"),
  fun.args = list(conf.int = 0.5),
  binwidth = 0.01,
  stackratio = 1.4,
  dotsize = 0.85,
  ylim = NULL,
  nBreaks = 4,
  axis.title.size = 20,
  axis.text.size = 16,
  xlab = "Trait",
  ylab = "Module Eigennode",
  save = TRUE,
  file = "ME_Trait_Dotplot.pdf",
  width = 6,
  height = 6,
  verbose = TRUE
)

Arguments

ME

A numeric of module eigennode values. ME must be in the same order as trait.

trait

A numeric of categorical sample trait values.

traitCode

A named numeric vector matching each trait level to a numeric value. Example: c("Control" = 0, "Treatment" = 1).

colors

A named character vector matching each trait level to a color. Example: c("Control" = "blue", "Treatment" = "red").

fun.data

A character(1) specifying the summary function to use. Potential values include median_hilow, mean_cl_boot, mean_cl_normal, and mean_sdl.

fun.args

A list giving additional arguments to the summary function.

binwidth

A numeric(1) specifying the maximum bin width.

stackratio

A numeric(1) indicating how far apart to stack the dots.

dotsize

A numeric(1) giving the size of the dots relative to binwidth.

ylim

A numeric(2) specifying the limits of the y-axis.

nBreaks

A numeric(1) giving the number of breaks on the y-axis.

axis.title.size

A numeric(1) indicating the size of the title text for both axes.

axis.text.size

A numeric(1) specifying the size of the text for both axes.

xlab

A character(1) giving the x-axis title.

ylab

A character(1) giving the y-axis title.

save

A logical(1) indicating whether to save the plot.

file

A character(1) giving the file name (.pdf) for the saved plot.

width

A numeric(1) specifying the width in inches of the saved plot.

height

A numeric(1) specifying the height in inches of the saved plot.

verbose

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

Value

A ggplot object.

Details

NA values in the trait are removed if present, along with corresponding ME values. Data is summarized like a box plot (median, Q1, Q3) by default, but can also be summarized with other methods. See ggplot2::stat_summary() for more details. A ggplot object is produced and can be edited outside of this function if desired.

See also

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

• getMEtraitCor() and plotMEtraitCor() to calculate and visualize all ME-trait correlations.

• plotMEtraitScatter() and plotMethTrait() for other methods to visualize a single ME-trait correlation.

Examples

if (FALSE) {

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

# Test Correlations between Module Eigennodes and Sample Traits
MEs <- modules$MEs
MEtraitCor <- getMEtraitCor(MEs, colData = colData, corType = "bicor",
                            file = "ME_Trait_Correlation_Stats.txt")
plotMEtraitCor(MEtraitCor, moduleOrder = moduleDendro$order,
               traitOrder = traitDendro$order,
               file = "ME_Trait_Correlation_Heatmap.pdf")

# Explore Individual ME-Trait Correlations
plotMEtraitDot(MEs$bisque4, trait = colData$Diagnosis_ASD,
               traitCode = c("TD" = 0, "ASD" = 1),
               colors = c("TD" = "#3366CC", "ASD" = "#FF3366"),
               ylim = c(-0.2,0.2), xlab = "Diagnosis",
               ylab = "Bisque 4 Module Eigennode",
               file = "bisque4_ME_Diagnosis_Dotplot.pdf")
plotMEtraitScatter(MEs$paleturquoise, trait = colData$Gran,
                   ylim = c(-0.15,0.15), xlab = "Granulocytes",
                   ylab = "Pale Turquoise Module Eigennode",
                   file = "paleturquoise_ME_Granulocytes_Scatterplot.pdf")
regions <- modules$regions
plotMethTrait("bisque4", regions = regions, meth = meth,
              trait = colData$Diagnosis_ASD,
              traitCode = c("TD" = 0, "ASD" = 1),
              traitColors = c("TD" = "#3366CC", "ASD" = "#FF3366"),
              trait.legend.title = "Diagnosis",
              file = "bisque4_Module_Methylation_Diagnosis_Heatmap.pdf")
}