Make facet plot of raw data
Usage
make_facet_plot(
data,
plot_category,
plot_treatment,
plot_sex,
pruned = "no",
current_type = "eEPSC",
y_variable = "P1",
x_label = "Time (min)",
treatment_colour_theme,
ggplot_theme = patchclampplotteR_facet_theme()
)
Arguments
- data
A dataframe containing the raw evoked current data generated from
make_normalized_EPSC_data()
. Ifpruned = "yes"
you must use the$individual_cells
component of a pruned dataset.- 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.- plot_sex
A character value ("Male" or "Female") corresponding to the sex you would like to plot.
- pruned
A character value (
"yes"
or"no"
) specifying if the data are pruned. The plot will then present the data as means with error bars.- 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 thepruned
argument to"yes"
. For spontaneous currents (current_type = "sEPSC"
), the available y_variables are"amplitude"
or"frequency"
.- x_label
A character value specifying the x-axis label. Defaults to "Time (min)".
- 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.
- 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 includetheme_bw()
,theme_classic()
or the name of a custom ggplot theme stored as an object.
Examples
# Raw eEPSC facet plots
make_facet_plot(sample_raw_eEPSC_df,
plot_category = 2,
plot_treatment = "Control",
plot_sex = "Male",
pruned = "no",
current_type = "eEPSC",
y_variable = "P1",
treatment_colour_theme = sample_treatment_names_and_colours,
ggplot_theme = patchclampplotteR_facet_theme()
)
# Pruned eEPSC facet plots
make_facet_plot(sample_pruned_eEPSC_df$individual_cells,
plot_category = 2,
plot_treatment = "Control",
plot_sex = "Male",
pruned = "yes",
current_type = "eEPSC",
y_variable = "mean_P1",
treatment_colour_theme = sample_treatment_names_and_colours,
ggplot_theme = patchclampplotteR_facet_theme()
)