create.pgs.with.continuous.phenotype.plot: Plot PGS Scatterplots

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

Plot PGS Scatterplots

Description

Create scatterplots for PGS data outputed by apply.polygenic.score() with continuous phenotype variables

Usage

create.pgs.with.continuous.phenotype.plot(
  pgs.data,
  phenotype.columns,
  hexbin.threshold = 1000,
  hexbin.colour.scheme = NULL,
  hexbin.colourkey = TRUE,
  hexbin.colourcut = seq(0, 1, length = 11),
  hexbin.mincnt = 1,
  hexbin.maxcnt = NULL,
  hexbin.xbins = 30,
  hexbin.aspect = 1,
  output.dir = NULL,
  filename.prefix = NULL,
  file.extension = "png",
  tidy.titles = FALSE,
  compute.correlation = TRUE,
  corr.legend.corner = c(0, 1),
  corr.legend.cex = 1.5,
  include.origin = FALSE,
  width = 10,
  height = 10,
  xaxes.cex = 1.5,
  yaxes.cex = 1.5,
  titles.cex = 1.5,
  point.cex = 0.75,
  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, and at least one continuous phenotype column. This function is designed to work with the output of apply.polygenic.score().
phenotype.columns	character vector of continuous phenotype column names in pgs.data to plot
hexbin.threshold	numeric threshold (exclusive) for cohort size at which to switch from scatterplot to hexbin plot.
hexbin.colour.scheme	character vector of colors for hexbin plot bins. Default is NULL which uses gray/black.
hexbin.colourkey	logical whether a legend should be drawn for a hexbinplot, defaults to TRUE.
hexbin.colourcut	numeric vector of values covering [0, 1] that determine hexagon colour class boundaries and hexagon legend size boundaries. Alternatively, an integer (<= hexbin.maxcnt) specifying the number of equispaced colourcut values in [0,1].
hexbin.mincnt	integer, minimum count for a hexagon to be plotted. Default is 1.
hexbin.maxcnt	integer, maximum count for a hexagon to be plotted. Cells with more counts are not plotted. Default is NULL.
hexbin.xbins	integer, number of bins in the x direction for hexbin plot. Default is 30.
hexbin.aspect	numeric, aspect ratio of hexbin plot to control plot dimensions. Default is 1.
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
compute.correlation	logical whether to compute correlation between PGS and phenotype and display in plot
corr.legend.corner	numeric vector indicating the corner of the correlation legend e.g. c(0,1) for top left
corr.legend.cex	numeric cex for correlation legend
include.origin	logical whether to include the origin (zero) in plot axes
width	numeric width of output plot in inches
height	numeric height of output plot in inches
xaxes.cex	numeric size for x-axis labels
yaxes.cex	numeric size for y-axis labels
titles.cex	numeric size for plot titles
point.cex	numeric size for plot points
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. If no continuous phenotype variables are detected, a warning is issued and NULL is returned.

Examples

set.seed(100);

pgs.data <- data.frame(
    PGS = rnorm(100, 0, 1),
    continuous.phenotype = rnorm(100, 2, 1)
    );
 temp.dir <- tempdir();

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

# Plot multiple PGS outputs

pgs.data$PGS.with.normalized.missing <- rnorm(100, 1, 1);
create.pgs.with.continuous.phenotype.plot(
    pgs.data,
    output.dir = temp.dir,
    filename.prefix = 'multiple-pgs',
    phenotype.columns = 'continuous.phenotype'
    );


# Plot multiple phenotypes

pgs.data$continuous.phenotype2 <- rnorm(100, 10, 1);
create.pgs.with.continuous.phenotype.plot(
    pgs.data,
    output.dir = temp.dir,
    filename.prefix = 'multiple-phenotypes',
    phenotype.columns = c('continuous.phenotype', 'continuous.phenotype2')
    );

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