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Plot Estimated Serodynamic Curves at Predictive or Population Level

Source: R/plot_serocurve.R
plot_serocurve.Rd

Plots the estimated antibody response curve derived from posterior samples of population-level (mu.par) or the predictive distribution from a fitted run_serodynamics() model. A median curve with an optional 95% credible interval ribbon is produced for each requested antigen-isotype and stratification combination.

Usage

plot_serocurve(
  model,
  antigen_iso = unique(model$Iso_type),
  strat = unique(model$Stratification),
  param_source = "predictive",
  show_ci = TRUE,
  log_y = FALSE,
  log_x = FALSE,
  xlim = NULL,
  facet_by_strat = FALSE,
  ...
)

Arguments

model

An sr_model object returned by run_serodynamics().

antigen_iso

A character vector of antigen-isotype combinations to plot. Defaults to all antigen-isotypes present in the subject-level draws of model (model$Iso_type); in normal usage these match the levels available in attr(model, "population_params").

strat

A character vector of stratification levels to include. Defaults to all stratification levels present in the subject-level draws of model (model$Stratification); in normal usage these match the levels available in attr(model, "population_params").

param_source

character; which posterior samples to use for the curve. Options:

  • "predictive" (default): uses the predictive distribution for a new individual drawn from the population-level prior.

  • "population": uses population-level mu.par samples stored in attr(model, "population_params"). Requires the model to have been fitted with run_serodynamics(..., with_pop_params = TRUE).

show_ci

logical; if TRUE (default), draws a 95% credible interval ribbon around the median curve.

log_y

logical; if TRUE, applies a log10 transformation to the y-axis.

log_x

logical; if TRUE, applies a log10 transformation to the x-axis.

xlim

(Optional) A numeric vector of length 2 providing custom x-axis limits.

facet_by_strat

logical; if TRUE, facets the plot by stratification level. When FALSE (default), different stratification levels are shown as different colours on the same panel.

...

Arguments passed on to add_serocurve_facets

facet_by_antigen_iso

logical; if TRUE, facets the plot by antigen-isotype. Defaults to TRUE when multiple antigen-isotypes are requested.

ncol

integer; number of columns when faceting. If NULL (default), a sensible value is chosen automatically.

Value

A ggplot2::ggplot object.

Examples

# nepal_sees_jags_output already includes population_params
model <- serodynamics::nepal_sees_jags_output

# Predictive curve for a single antigen-isotype and stratum
p1 <- plot_serocurve(
  model       = model,
  antigen_iso = "HlyE_IgA",
  strat       = "typhi"
)
print(p1)


# Predictive curves for both stratifications, colored by stratum
p2 <- plot_serocurve(
  model       = model,
  antigen_iso = "HlyE_IgA"
)
print(p2)


# Predictive curve faceting by stratification instead of coloring
p3 <- plot_serocurve(
  model          = model,
  antigen_iso    = "HlyE_IgA",
  facet_by_strat = TRUE
)
print(p3)


# Population level curve for multiple antigen-isotypes, faceted, without CI
p4 <- plot_serocurve(
  model                = model,
  antigen_iso          = c("HlyE_IgA", "HlyE_IgG"),
  param_source = "population",
  facet_by_antigen_iso = TRUE,
  show_ci              = FALSE
)
print(p4)


# Population level distribution
p5 <- plot_serocurve(
  model        = model,
  antigen_iso  = "HlyE_IgA",
  param_source = "population"
)
print(p5)