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Bioenergetic Scope Plot

Source: R/bioscope_plot.R
bioscope_plot.Rd

Generate the Bioenergetic Scope Plot

Usage

bioscope_plot(
  energetics,
  model = "ols",
  error_bar = "ci",
  conf_int = 0.95,
  size = 2,
  basal_shape = 1,
  max_shape = 19,
  group_label = "Experimental Group",
  sep_reps = FALSE,
  ci_method = "Wald"
)

Arguments

energetics

A table of calculated glycolysis and OXPHOS rates. Returned by get_energetics

model

The linear model used to estimate mean and confidence intervals: ordinary least squares ("ols") or mixed-effects ("mixed")

error_bar

Whether to plot error bars as standard deviation ("sd") or confidence intervals ("ci")

conf_int

The confidence interval percentage. Should be between 0 and 1

size

Size of the points

basal_shape

Shape of the points for basal values

max_shape

Shape of the points for max values

group_label

Label for the experimental group to populate the legend title

sep_reps

Whether to calculate summary statistics on the groups with replicates combined. The current default FALSE combines replicates, but future releases will default to TRUE providing replicate-specific summaries.

ci_method

The method used to compute confidence intervals for the mixed-effects model: "Wald", "profile", or "boot" passed to lme4::confint.merMod().

bioscope_plot

Creates a 2D plot visualizing the mean and standard deviation basal and maximal ATP production from glycolysis and OXPHOS for each experimental group

Value

a ggplot

Examples

rep_list <- system.file("extdata", package = "ceas") |>
  list.files(pattern = "*.xlsx", full.names = TRUE)
seahorse_rates <- read_data(rep_list, sheet = 2)
partitioned_data <- partition_data(seahorse_rates)
energetics <- get_energetics(
  partitioned_data,
  ph = 7.4,
  pka = 6.093,
  buffer = 0.1
)
bioscope_plot(energetics, sep_reps = FALSE)


# to change fill, the geom_point shape should be between 15 and 20.
# These shapes are filled without border and will correctly show on the legend.
bioscope_plot(
  energetics,
  sep_reps = TRUE,
  size = 3,
  basal_shape = 2,
  max_shape = 17 # empty and filled triangle
) +
  ggplot2::scale_fill_manual(
    values = c("#e36500", "#b52356", "#3cb62d", "#328fe1")
  )


# to change color, use ggplot2::scale_color_manual
bioscope_plot(energetics, sep_reps = FALSE) +
  ggplot2::scale_color_manual(
    values = c("#e36500", "#b52356", "#3cb62d", "#328fe1")
  )