Graph estimated antibody decay curves

Description

Graph estimated antibody decay curves

Usage

graph.curve.params(
  object,
  antigen_isos = unique(object\$antigen_iso),
  verbose = FALSE,
  quantiles = c(0.1, 0.5, 0.9),
  alpha_samples = 0.3,
  chain_color = TRUE,
  log_x = FALSE,
  log_y = TRUE,
  n_curves = 100,
  iters_to_graph = head(unique(object\$iter), n_curves),
  ...
)

Arguments

object a data.frame() containing MCMC samples of antibody decay curve parameters
antigen_isos antigen isotypes to analyze (can subset object)
verbose verbose output
quantiles Optional numeric vector of point-wise (over time) quantiles to plot (e.g., 10%, 50%, and 90% = c(0.1, 0.5, 0.9)). If NULL, no quantile lines are shown.
alpha_samples alpha parameter passed to ggplot2::geom_line (has no effect if iters_to_graph is empty)
chain_color logical: if TRUE (default), MCMC chain lines are colored by chain. If FALSE, all MCMC chain lines are black.
log_x should the x-axis be on a logarithmic scale (TRUE) or linear scale (FALSE, default)?
log_y should the Y-axis be on a logarithmic scale (default, TRUE) or linear scale (FALSE)?
n_curves how many curves to plot (see details).
iters_to_graph which MCMC iterations in curve_params to plot (overrides n_curves).
… not currently used

Details

Fixed … arguments

The arguments fun, n, and args are set internally and cannot be overridden via …. Passing them will trigger an informative error.

n_curves and iters_to_graph

In most cases, object will contain too many rows of MCMC samples for all of these samples to be plotted at once.

  • Setting the n_curves argument to a value smaller than the number of rows in curve_params will cause this function to select the first n_curves rows to graph.

  • Setting n_curves larger than the number of rows in ’ will result all curves being plotted.

  • If the user directly specifies the iters_to_graph argument, then n_curves has no effect.

Value

a ggplot2::ggplot() object showing the antibody dynamic kinetics of selected antigen/isotype combinations, with optional posterior distribution quantile curves.

Examples

Code
library("serocalculator")

# Load example dataset
curve <- typhoid_curves_nostrat_100 |>
  dplyr::filter(antigen_iso %in% c("HlyE_IgA", "HlyE_IgG"))

# Plot quantiles without showing all curves
plot1 <- graph.curve.params(curve, n_curves = 0)
print(plot1)

Code
# Plot with additional quantiles and show all curves
plot2 <- graph.curve.params(
  curve,
  n_curves = Inf,
  quantiles = c(0.1, 0.5, 0.9)
)
print(plot2)

Code
# Plot with MCMC chains in black
plot3 <- graph.curve.params(
  curve,
  n_curves = Inf,
  quantiles = c(0.1, 0.5, 0.9),
  chain_color = FALSE
)
print(plot3)