ChAT Project

Introduction

These are the analysis files used in the following publication:

• Taylor R Fore et al. "Acetylcholine modulates cerebellar granule cell spiking by regulating the balance of synaptic excitation and inhibition" Journal of Neuroscience 1 April 2020, DOI: https://doi.org/10.1523/JNEUROSCI.2148-19.2020

How to Use

Requirements

• R language: R (R >= 3.2.0)
• R package: matools
• R package: googlesheets4 (required if running the scripts as CRON jobs)
• R package: utils (core package - required if running the scripts as CRON jobs)
• RStudio: RStudio (IDE for interactive analysis)

Running Workflows

1. The workflow scripts in the repository are fully automated and expect the directory structure as follows:

├── analysis_scripts
│   ├── evoked_ap_analysis.R
│   └── evoked_psp_analysis.R
├── data
│   ├── cell_attached_grc_evoked_ap
│   │   ├── chat_evoked_ap_parameters.csv
│   │   └── data
│   │       ├── rec000000.ASC
│   │       ├── rec000000.txt
│   │       ...
│   │       ├── rec00000x.ASC
│   │       └── rec00000x.txt
│   └── evoked_psp
│       ├── chat_evoked_psp_parameters.csv
│       └── data
│           ├── rec000000.ASC
│           ...
│           └── rec00000x.ASC

2. Clone the repository and change into the analysis_scripts directory

$ git clone https://github.com/trfore/chat-project.git
$ cd chat-project

3. Run the scripts. PDF figures are placed within the parent directory, chat-project.

# Evoked Granule Cell Action Potential Analysis
Rscript analysis_scripts/evoked_ap_analysis.R

# Evoked Post-Synaptic Potential Analysis
Rscript analysis_scripts/evoked_psp_analysis.R

4. Alternatively, interactively run these scripts within RStudio.

Running Workflows as CRON jobs

1. Modify a workflow by changing the following:

# Project Data Processing ----
# Local data files
data_path <- paste(getwd(), "data/evoked_psp", sep = "/")
data_folder <- paste(data_path, "data", sep = "/")

# Option 1: Using local parameter sheet
data_parameters <- paste(data_path, "chat_evoked_psp_parameters.csv", sep = "/")

# Option 2: Using publicly shared Google Sheet
googlesheets4::gs4_deauth()
public_sheet <- "https://docs.google.com/spreadsheets/d/YOUR_SHEET_HASH_HERE/edit?usp=sharing"
data_parameters <-
  googlesheets4::read_sheet(public_sheet)

# Import the parameters
import_experiment_parameters(data_parameters)

2. Create a cron job

# crontab file
# run daily at midnight
0 0 * * * cd /home/chat-project/analysis_scripts; Rscript evoked_ap_analysis.R >/dev/null 2>&1
# run daily at 12:30 am
30 0 * * * cd /home/chat-project/analysis_scripts; Rscript evoked_psp_analysis.R >/dev/null 2>&1

Authors

• Taylor Fore (https://github.com/trfore)

References

• Fore et al. 2020
• https://github.com/trfore/matools
• https://github.com/trfore/chat-project
• https://github.com/trfore/chatmodel
• https://www.r-project.org/
• https://www.rstudio.com/

R packages

• https://github.com/tidyverse/googlesheets4/
• https://github.com/HenrikBengtsson/R.utils