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Generate a Unified Line Plot for PK Data

Source: R/g_lineplot.R
g_lineplot.Rd

This function creates a ggplot2 line plot for pharmacokinetic (PK) data. It is designed to be flexible and can generate plots for both individual concentration-time profiles and mean concentration-time profiles. The function supports various customizations including log scales, faceting, error bars (for mean plots), and threshold lines.

Usage

g_lineplot(
  data,
  x_var,
  y_var,
  color_by,
  facet_by = NULL,
  ylog_scale = FALSE,
  threshold_value = NULL,
  dose_data = NULL,
  palette = NULL,
  sd_min = FALSE,
  sd_max = FALSE,
  ci = FALSE,
  tooltip_vars = NULL,
  labels_df = NULL
)

Arguments

data

A data.frame containing the data to be plotted. This should be pre-processed by either process_data_individual or process_data_mean.

x_var

A character string specifying the column name for the x-axis.

y_var

A character string specifying the column name for the y-axis.

color_by

A character vector specifying the column(s) from the original dataset that are used to determine the color of the lines and points.

facet_by

A character vector of column names to facet the plot by. Default is NULL for no faceting.

ylog_scale

A logical value (TRUE or FALSE) indicating whether to use a logarithmic scale for the y-axis.

threshold_value

A numeric value for the y-intercept of the threshold line. Only used if show_threshold is TRUE.

dose_data

An optional data.frame containing dosing information. If not NULL, dose lines will be added. Default is NULL. The data frame must contain the faceting variables (if any are used) and a TIME_DOSE column for the x-intercepts.

palette

An optional named character vector of colors for the plot. The names should correspond to the levels of the color_var in the data. This is typically generated by get_persistent_palette.

sd_min

A logical value (TRUE or FALSE). If TRUE, plots the lower standard deviation error bars. (Only for mean plots).

sd_max

A logical value (TRUE or FALSE). If TRUE, plots the upper standard deviation error bars. (Only for mean plots).

ci

A logical value (TRUE or FALSE). If TRUE, plots a 95% confidence interval ribbon. (Only for mean plots).

tooltip_vars

Character vector of column names to include in the tooltip.

labels_df

A data.frame for variable label lookups.

Value

A ggplot object representing the line plot.

Plot Types

The function's behavior changes based on the arguments provided, for two main plot types:

  • Individual Plots: Set y_var = "AVAL" The input data should be from process_data_individual.

  • Mean Plots: Set y_var = "Mean" The input data should be from process_data_mean. The arguments sd_min, sd_max, and ci are only applicable to this plot type.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
ind_data <- expand.grid(
  time_var = c(0, 1, 2, 4, 8, 12),
  USUBJID = c("Subject1", "Subject2")
) %>%
  mutate(
    AVAL = ifelse(USUBJID == "Subject1", 50, 80) * exp(-0.5 * time_var) + rnorm(n(), 0, 1),
    PARAM = "Analyte1",
    DOSEA = "Dose 1",
    RRLTU = "hours",
    AVALU = "ng/mL"
  )

 p <- g_lineplot(
   data = ind_data,
   x_var = "time_var",
   y_var = "AVAL",
   color_by = "USUBJID"
   )
print(p)