inst/workflow_examples/example_whole_well_analysis_script.R

In MEAanalysis: Analyse and Visualise Multi Electrode Array Burst Data

############################################################################################

### Example script for creating a bar chart of calculated MEA parameters grouped by well ###

############################################################################################

# Following code reads in electrode burst dataset produced by the axis navigator software in csv format and processes for use in analysis
# User to update the data_path (direct to electrode burst dataset) and recording identifier (used to determine time interval within specific recording)

test_data_1 <- create_electrode_dataset(data_path = system.file("extdata", "input_electrode_burst.csv", package = "MEAanalysis"),
                                        recording_identifier = "test_data_1")
test_data_2 <- create_electrode_dataset(data_path = system.file("extdata", "comparison_agonist_challenge_electrode_burst_list.csv", package = "MEAanalysis"),
                                        recording_identifier = "test_data_2")

# Following code merges datasets together vertically (list datasets for use in analysis in the rbind function, use examples below to update code)
# Rerun code if with to refresh dataset used to create barchart
# e.g., output_table <- rbind(test_data_1)
# e.g., output_table <- rbind(test_data_1, test_data_2)

output_table <- rbind(test_data_1, test_data_2)

# Following code calculates a chosen parameter for a specific time interval and recordings by well
# new columns will be added to the dataset each time a function is run (run above rbind function to refresh)
# update time interval (s) and recording identifier accordingly i.e., function(data, time_lower_bound, time_upper_bound, recording_identifier)

# output_table <- number_of_bursts() #calculates he mean, sd, and se  number of bursts within a given time interval by an electrode for each well (for a specific recording)
# output_table <- burst_duration() #calculates the mean, sd, and se burst duration within a given time interval for each well (for a specific recording)
# output_table <- spikes_per_burst() #calculates mean, sd, and se number of spikes per burst within a given time interval for each well (for a specific recording)
# output_table <- mean_burst_ISI() #calculates average, sd, and se mean ISI within a burst (sec) for a given time interval for each well (for a specific recording)

# EXAMPLE CODE: calculates parameters for each  well within the given time interval for a recording

output_table <- well_burst_duration(data = output_table, 0, 30, recording_identifier = "test_data_1")
output_table <- well_burst_duration(data = output_table, 30, 60, recording_identifier = "test_data_1")
output_table <- well_burst_duration(data = output_table, 60, 90, recording_identifier = "test_data_1")
output_table <- well_burst_duration(data = output_table, 60, 90, recording_identifier = "test_data_2")

output_table <- well_spikes_per_burst(data = output_table, 0, 30, recording_identifier = "test_data_1")
output_table <- well_spikes_per_burst(data = output_table, 30, 60, recording_identifier = "test_data_1")
output_table <- well_spikes_per_burst(data = output_table, 60, 90, recording_identifier = "test_data_1")
output_table <- well_spikes_per_burst(data = output_table, 60, 90, recording_identifier = "test_data_2")

output_table <- well_mean_burst_ISI(data = output_table, 0, 30, recording_identifier = "test_data_1")
output_table <- well_mean_burst_ISI(data = output_table, 30, 60, recording_identifier = "test_data_1")
output_table <- well_mean_burst_ISI(data = output_table, 60, 90, recording_identifier = "test_data_1")
output_table <- well_mean_burst_ISI(data = output_table, 60, 90, recording_identifier = "test_data_2")

output_table <- well_number_of_bursts(data = output_table, 0, 30, recording_identifier = "test_data_1")
output_table <- well_number_of_bursts(data = output_table, 30, 60, recording_identifier = "test_data_1")
output_table <- well_number_of_bursts(data = output_table, 60, 90, recording_identifier = "test_data_1")
output_table <- well_number_of_bursts(data = output_table, 60, 90, recording_identifier = "test_data_2")

# Following code creates a bar chart of the calculated MEA parameter grouped by well
# User to update function arguments accordingly ii.e., well_barchart(data, well_parameter, well_filter, statistic)
# For well_parameter argument include "number_of_bursts"/ "burst_duration"/ "spikes_per_burst"/ "mean_burst_ISI"

p <- well_barchart(data = output_table, well_parameter = "burst_duration", well_filter = "A1|A2|A3|A4", statistic = se)
print(p)
p <- well_barchart(data = output_table, well_parameter = "spikes_per_burst", well_filter = "A1|A2|A3|A4", statistic = se)
print(p)
p <- well_barchart(data = output_table, well_parameter = "mean_burst_ISI", well_filter = "A1|A2|A3|A4", statistic = se)
print(p)
p <- well_barchart(data = output_table, well_parameter = "number_of_bursts", well_filter = "A1|A2|A3|A4", statistic = se)
print(p)