Make paired-pulse ratio (PPR) dataframe for before vs. after comparisons

This function filters the raw current data into data that belong to one of two time points. They are the baseline period and a user-specified interval after a hormone or protocol has been applied. The "before/after" comparison of the paired-pulse ratio (PPR) is useful to determine which mechanism is involved in modifying synaptic plasticity. For example, the PPR may be related to the probability of neurotransmitter release Oleskevich et al., 2000.

Usage

make_PPR_data(
  data,
  include_all_treatments = "yes",
  list_of_treatments = NULL,
  PPR_min = 0,
  PPR_max = 5,
  baseline_interval = "t0to5",
  post_hormone_interval = "t20to25",
  treatment_colour_theme,
  save_output_as_RDS = "no"
)

Arguments

data: A dataframe containing the raw evoked current data generated from make_normalized_EPSC_data().
include_all_treatments: A character ("yes" or "no") specifying if the plot will include data from all treatments. If "no", you must specify a list of treatments in list_of_treatments.
list_of_treatments: A list of character values describing the treatments that will be in the plot. Defaults to NULL, since include_all_treatments is "yes" by default.
PPR_min: A numeric value representing the minimum PPR value permitted in the filtered dataset. Defaults to 0.
PPR_max: A numeric value representing the maximum PPR value permitted in the filtered dataset. Defaults to 5.
baseline_interval: A character value indicating the name of the interval used as the baseline. Defaults to "t0to5", but can be changed. Make sure that this matches the baseline interval that you set in make_normalized_EPSC_data().
post_hormone_interval: A character value specifying the interval used for the data points after a hormone or protocol was applied.
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_output_as_RDS: A character ("yes" or "no") describing if the resulting object should be saved as an RDS file in the raw data folder.

Value

A dataframe containing all of the columns from make_normalized_EPSC_data(), but filtered to only include PPR values between PPR_min and PPR_max within the baseline_interval and post_hormone_interval.

Examples


make_PPR_data(
  data = sample_raw_eEPSC_df,
  include_all_treatments = "yes",
  list_of_treatments = NULL,
  PPR_min = 0,
  PPR_max = 5,
  baseline_interval = "t0to5",
  post_hormone_interval = "t20to25",
  treatment_colour_theme = sample_treatment_names_and_colours
)
#> # A tibble: 2,205 × 21
#> # Groups:   letter [19]
#>    letter synapses  sex   treatment  time ID          P1    P2     X     Y   age
#>    <fct>  <fct>     <fct> <fct>     <dbl> <fct>    <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 AO     Glutamate Male  Control    0    23623002  17.4  78.4    NA    NA    39
#>  2 AO     Glutamate Male  Control    0.08 23623002  24.1  58.9    NA    NA    39
#>  3 AO     Glutamate Male  Control    0.17 23623002  35.6  60.0    NA    NA    39
#>  4 AO     Glutamate Male  Control    0.25 23623002  15.8  32.3    NA    NA    39
#>  5 AO     Glutamate Male  Control    0.33 23623002  53.9  26.4    NA    NA    39
#>  6 AO     Glutamate Male  Control    0.42 23623002  45.5  74.8    NA    NA    39
#>  7 AO     Glutamate Male  Control    0.5  23623002  28.1  69.6    NA    NA    39
#>  8 AO     Glutamate Male  Control    0.58 23623002  27.8  62.0    NA    NA    39
#>  9 AO     Glutamate Male  Control    0.67 23623002  60.0  52.7    NA    NA    39
#> 10 AO     Glutamate Male  Control    0.75 23623002  46.9  60.3    NA    NA    39
#> # ℹ 2,195 more rows
#> # ℹ 10 more variables: animal <dbl>, category <fct>, cell <chr>, PPR <dbl>,
#> #   interval <fct>, baseline_range <lgl>, baseline_mean <dbl>,
#> #   P1_transformed <dbl>, P2_transformed <dbl>, state <chr>