MEA Analysis Package

This package provides tools for analyzing Microelectrode Array (MEA) data. It includes three main classes: MEAnalysis, BatchMEAnalysis, and ElectrodeBursts.

For examples on how to use the package, see the scripts in the /main directory.

Installation

To install the MEA Analysis package, you can use the devtools package in R. If you don't have devtools installed, you can install it first:

install.packages("devtools")

Then, you can install the MEA Analysis package directly from GitHub:

devtools::install_github("stevensusas/MEAnalysis")

After installation, load the package in your R session:

library(MEAnalysis)

Classes

MEAnalysis

The MEAnalysis class is the core of the package, providing methods for processing and analyzing MEA data.

Key methods:

1. treatment_averages_t_test_plot(control, groups_to_plot, title = NULL)
   • Parameters:
     • control: character - The name of the control group
     • groups_to_plot: character vector - Names of groups to include in the plot
     • title: character (optional) - The title of the plot
   • Returns: ggplot object - A plot representing the t-test results for treatment averages

BatchMEAnalysis

The BatchMEAnalysis class extends MEAnalysis to handle batch processing of multiple MEA data files.

Key methods:

1. run_mea_analysis(conditions, metric, control_condition = NULL, title = NULL)

   • Parameters:
     • conditions: character vector - Conditions to analyze
     • metric: character - The specific metric to analyze
     • control_condition: character (optional) - The control condition to compare against
     • title: character (optional) - The title of the plot
   • Returns: ggplot object - A plot representing the MEA analysis results

2. generate_significance_overview(control_group, groups_to_include = NULL, metrics_to_visualize = NULL, title)

   • Parameters:
     • control_group: character - The control group to compare against
     • groups_to_include: character vector (optional) - Specific groups to include in the analysis
     • metrics_to_visualize: character vector (optional) - Specific metrics to visualize
     • title: character - The title of the heatmap
   • Returns: data.frame - A significance overview table

ElectrodeBursts

The ElectrodeBursts class focuses on processing and visualizing electrode burst data.

Key methods:

1. create_comparison_raster_plot(control_group, treatments_array, plot_title)
   • Parameters:
     • control_group: character - The control group to be included in the comparison
     • treatments_array: character vector - An array of treatment names to compare
     • plot_title: character - The title of the plot
   • Returns: ggpubr object - A combined raster plot comparing multiple treatments

Usage

To use this package, start by initializing the appropriate class with your data file(s):

# For single file analysis
mea_analysis <- MEAnalysis$new("path/to/your/file.csv")

# For batch analysis
batch_analysis <- BatchMEAnalysis$new(list_of_file_paths)

# For electrode burst analysis
electrode_bursts <- ElectrodeBursts$new("path/to/your/file.csv")

Then, you can use the various methods provided by each class to analyze your data and generate plots. Here are some examples:

MEAnalysis

# Create a treatment averages t-test plot
plot <- mea_analysis$treatment_averages_t_test_plot(
  "Control",
  c("Treatment1", "Treatment2"),
  "Treatment Averages T-Test Plot"
)
# plot is a ggplot object

BatchMEAnalysis

# Run MEA analysis
plot <- batch_analysis$run_mea_analysis(
  c("Control", "Treatment1", "Treatment2"),
  "MeanFiringRate",
  "Control",
  "MEA Analysis Results"
)
# plot is a ggplot object

# Generate significance overview
overview <- batch_analysis$generate_significance_overview(
  "Control",
  c("Treatment1", "Treatment2"),
  c("MeanFiringRate", "BurstFrequency"),
  "Significance Overview"
)
# overview is a data.frame containing the significance overview

ElectrodeBursts

# Create a comparison raster plot
plot <- electrode_bursts$create_comparison_raster_plot(
  "Control",
  c("Treatment1", "Treatment2"),
  "Comparison Raster Plot"
)
# plot is a ggpubr object

Contributing

Contributions to improve the package are welcome. Please submit issues and pull requests on the project's GitHub repository.

License

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