Make a summary plot for a specific treatment

This function enables you to create a scatterplot of mean evoked (or spontaneous) current amplitude over over time in minutes. The data are summarized by treatment and sex, and averaged per minute. The data are presented as mean +/- the standard error.

Usage

plot_summary_current_data(
  data,
  plot_category = 2,
  plot_treatment = "Control",
  current_type = "eEPSC",
  y_variable = "amplitude",
  hormone_added = "Insulin",
  hormone_or_HFS_start_time = 5,
  legend_position = "right",
  legend_position_inside = c(0.13, 0.15),
  included_sexes = "both",
  male_label = "Male",
  female_label = "Female",
  include_representative_trace = "no",
  representative_trace_filename = NULL,
  position_dodge_size = 0,
  annotation_x_min = 1,
  annotation_x_max = 8,
  annotation_y_min = 0,
  annotation_y_max = 40,
  y_axis_limit,
  signif_stars = "no",
  significance_display_method = "stars",
  geom_signif_text_size = 5,
  geom_signif_family = "",
  t_test_df,
  large_axis_text = "no",
  shade_intervals = "no",
  theme_options,
  treatment_colour_theme,
  save_plot_png = "no",
  ggplot_theme = patchclampplotteR_theme()
)

Arguments

data: A dataframe containing pruned summary data for all cells. This is the third element of the list generated from make_pruned_EPSC_data().
plot_category: A numeric value specifying the category, which can be used to differentiate different protocol types. In the sample dataset for this package, plot_category == 2 represents experiments where insulin was applied continuously after a 5-minute baseline period.
plot_treatment: A character value specifying the treatment you would like to plot (e.g. "Control"). plot_treatment represents antagonists that were present on the brain slice, or the animals were fasted, etc.
current_type: A character describing the current type. Allowed values are "eEPSC" or "sEPSC".
y_variable: A character value specifying the variable to be plotted on the y-axis. For evoked currents (current_type = "eEPSC"), the available y_variables are "P1", "P1_transformed", "mean_P1" and "PPR". Note: If you select "mean_P1", you must set the pruned argument to "yes". For spontaneous currents (current_type = "sEPSC"), the available y_variables are "amplitude" or "frequency".
hormone_added: A character value that will be used as the label over the line annotating the period when a hormone was applied. Examples include "500 nM Insulin", "CCK + Leptin", and "Insulin". If you applied a high-frequency stimulation (HFS) protocol instead, write "HFS", and an annotation arrow will be added instead.
hormone_or_HFS_start_time: A numeric value indicating the time (in minutes) when a hormone was added or when HFS was applied. This will set the annotation line start point.
legend_position: A character value ("left", "right", "top", "bottom", "inside") which describes the location of the legend. If you set this to "inside", you may need to adjust the location of the representative trace with annotation_x_min, annotation_x_max, etc. Or, you can choose to insert the representative trace as a separate geom using the patchwork package (e.g. set up a two-row patchwork with the representative trace in the top row, and the summary plot in the second row).
legend_position_inside: A list of two numeric values describing the coordinates of the legend. This only applies if legend_position = "inside".
included_sexes: A character value ("both", "male" or "female"). Useful if you want to have a plot with data from one sex only. Defaults to "both". If you choose a single sex, the resulting plot will have "-males-only" or "-females-only" in the file name. WARNING!! If you choose "male" or "female", you MUST ensure that the t_test_df contains data that has been filtered to only include one sex. Otherwise, the significance stars will represent both sexes and it will be inaccurate.
male_label: A character value used to describe how males are encoded in the sex column of the dataframe used in data. This MUST match the value for male data in the sex column, and it must be consistent across data sheets. Defaults to "Male".
female_label: A character value used to describe how females are encoded in the sex column of the dataframe used in data. This MUST match the value for female data in the sex column, and it must be consistent across data sheets. This must be consistent in all data sheets. Defaults to "Female".
include_representative_trace: A character ("yes" or "no") describing if a representative trace should be included as an overlay to the plot. This pulls from a png file stored in Figures/Representative-Traces/". Please specify the file-name in representative_trace_filename.
representative_trace_filename: A character value describing the filename of the representative trace. This should be the name of a .png file. Use relative paths to specify files. For example, a figure in the Figures/Representative-Traces subfolder would be entered as representative_trace_filename = "Figures/Representative-Traces/Category-2-Control-Trace.png".
position_dodge_size: A numeric value describing the distance that points should be dodged through ggplot2::position_dodge(). Defaults to 0.1.
annotation_x_min: A numeric value describing the minimum value on the x-axis for the representative trace. Defaults to 1, which will place it at the lower left corner of the plot (when combined with the default value for annotation_y_min).
annotation_x_max: A numeric value describing the maximum value on the x-axis for the representative trace. Change this if your representative trace image looks squished or stretched.
annotation_y_min: A numeric value describing the minimum value on the y-axis for the representative trace. Defaults to 0, which will place it at the lower left corner of the plot (when combined with the default value for annotation_x_min).
annotation_y_max: A numeric value describing the maximum value on the y-axis for the representative trace. Change this if your representative trace image looks squished or stretched.
y_axis_limit: A numeric value describing the maximum value on the y-axis.
signif_stars: A character ("yes" or "no") describing if significance stars should be included as an overlay in the plot. If "yes", you must specify a dataframe containing the results of a t-test, which is generated using perform_t_tests_for_summary_plot(). NOTE! If included_sexes is "male" or "female", you MUST use a t-test that was performed on data filtered to ONE sex.
significance_display_method: A character value ("stars" or "p-value") describing how significance values should be displayed. These annotations will not appear if signif_stars is "no".)
geom_signif_text_size: A numeric value describing the size of the text annotations (significance stars or p-values) on the plot. Defaults to 8.
geom_signif_family: A character value describing the font family used for the p-value annotations used by ggsignif::geom_signif(). Defaults to "" (empty, will use default system font), but can be replaced with a named font. Use a package like extrafont to load system fonts into R.
t_test_df: A dataframe of t-test results, which has been generated using perform_t_tests_for_summary_plot(). Important note! The t-test dataframe must be filtered to match the same conditions in the data argument, or the significance stars will be misleading.
large_axis_text: A character ("yes" or "no"). If "yes", a ggplot theme layer will be applied which increases the size of the axis text.
shade_intervals: A character ("yes" or "no"). If "yes", a ggplot theme layer will be applied which adds lightly shaded rectangles to highlight 5-minute intervals.
theme_options: A dataframe containing theme options. See sample_theme_options for an example of what this dataframe should look like.
treatment_colour_theme: A dataframe containing treatment names and their associated colours as hex values. See sample_treatment_names_and_colours for an example of what this dataframe should look like.
save_plot_png: A character ("yes" or "no"). If "yes", the plot will be saved as a .png using ggsave. The filepath depends on the current type, but they will all go in subfolders below Figures/ in your project directory.
ggplot_theme: The name of a ggplot theme or your custom theme. This will be added as a layer to a ggplot object. The default is patchclampplotteR_theme(), but other valid entries include theme_bw(), theme_classic() or the name of a custom ggplot theme stored as an object.

Value

A ggplot object. If save_plot_png == "yes", it will also generate a .png file exported to Figures/Evoked-currents/Output-summary-plots or Figures/Spontaneous-currents/Output-summary-plots, depending on the current_type. The .png filename will be in this format: "Summary-plot-plot_treatment-category-plot_category-file_name_ending-text_size-sexes.png". The text_size will only be added on if you are using large_axis_text ("LARGE" will be included in the filename). The file_name_ending will be automatically added on for spontaneous current data to specify what y_variable is plotted (e.g. "raw_amplitude"). The sexes will only be added if you choose to plot a single sex. For example, if you set included_sexes = "Male", the .png filename will have "-males-only" included in the filename.

Example auto-generated filenames include:

"Summary-plot-Control-category-2.png"
"Summary-plot-Control-category-2-males-only.png"
"Summary-plot-Control-category-2_raw_amplitude.png" for spontaneous currents.

Examples


plot_summary_current_data(
  data = sample_pruned_eEPSC_df$all_cells,
  plot_category = 2,
  plot_treatment = "Control",
  current_type = "eEPSC",
  y_variable = "amplitude",
  hormone_added = "Insulin",
  hormone_or_HFS_start_time = 5,
  included_sexes = "both",
  include_representative_trace = "yes",
  representative_trace_filename = import_ext_data("Control-trace.png"),
  y_axis_limit = 175,
  signif_stars = "yes",
  t_test_df = sample_eEPSC_t_test_df,
  large_axis_text = "no",
  shade_intervals = "no",
  treatment_colour_theme = sample_treatment_names_and_colours,
  theme_options = sample_theme_options
)
#> Warning: Removed 25 rows containing missing values or values outside the scale range
#> (`geom_segment()`).

Usage

Arguments

Value

See also

Examples