create.pgs.density.plot: Plot PGS Density

In ApplyPolygenicScore: Utilities for the Application of a Polygenic Score to a VCF

Plot PGS Density

Description

Plot density curves of PGS data outputted by apply.polygenic.score. If phenotype columns are provided, multiple density curves are plotted for automatically detected categories for each categorical variable.

Usage

create.pgs.density.plot(
  pgs.data,
  phenotype.columns = NULL,
  output.dir = NULL,
  filename.prefix = NULL,
  file.extension = "png",
  tidy.titles = FALSE,
  width = 10,
  height = 10,
  xaxes.cex = 1.5,
  yaxes.cex = 1.5,
  titles.cex = 1.5,
  key.cex = 1,
  border.padding = 1
)

Arguments

pgs.data	data.frame PGS data as formatted by apply.polygenic.score(). Required columns are at least one of PGS, PGS.with.replaced.missing, or PGS.with.normalized.missing. This function is designed to work with the output of apply.polygenic.score().
phenotype.columns	character vector of phenotype columns in pgs.data to plot (optional)
output.dir	character directory to save output plots
filename.prefix	character prefix for output filenames
file.extension	character file extension for output plots
tidy.titles	logical whether to reformat PGS plot titles to remove periods
width	numeric width of output plot in inches
height	numeric height of output plot in inches
xaxes.cex	numeric size for all x-axis labels
yaxes.cex	numeric size for all y-axis labels
titles.cex	numeric size for all plot titles
key.cex	numeric size of color key legend
border.padding	numeric padding for plot borders

Value

If no output directory is provided, a multipanel lattice plot object is returned, otherwise a plot is written to the indicated path and NULL is returned.

Examples

set.seed(100);
pgs.data <- data.frame(
    PGS = rnorm(100, 0, 1)
    );
 temp.dir <- tempdir();

# Basic Plot
create.pgs.density.plot(
    pgs.data,
    output.dir = temp.dir,
    filename.prefix = 'basic-plot',
    width = 6,
    height = 6
    );

# Plot multiple PGS outputs
pgs.data$PGS.with.normalized.missing <- rnorm(100, 1, 1);
create.pgs.density.plot(pgs.data, output.dir = temp.dir);

# Plot phenotype categories

pgs.data$sex <- sample(c('male', 'female', 100, replace = TRUE));
create.pgs.density.plot(
    pgs.data,
    output.dir = temp.dir,
    filename.prefix = 'multiple-pgs',
    phenotype.columns = 'sex'
    );

# Plot multiple phenotypes

pgs.data$letters <- sample(letters[1:5], 100, replace = TRUE);
create.pgs.density.plot(
    pgs.data,
    output.dir = temp.dir,
    filename.prefix = 'multiple-phenotypes',
    phenotype.columns = c('sex', 'letters')
    );

ApplyPolygenicScore documentation built on April 4, 2025, 12:18 a.m.