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GitHub analysis repository organization

While there is no one "right" way to organize a GitHub repository, here's our suggested structure:

├── data
├── scripts
│   ├── preprocessing
│   ├── analysis
│   └── visualization
├── results
│   ├── figures
│   ├── tables
│   └── reports
├── docker
├── environment.yml
├── README.md
  • data: This directory contains analysis data, as well as metadata files. Please do not commit individual-level data to GitHub
  • scripts: This directory contains subdirectories for different types of scripts, such as preprocessing, analysis, and visualization.
  • results: This directory contains subdirectories for different types of results, such as figures, tables, and reports.
  • docker directory or environment.yml: The docker directory contains the Docker file for the reproducible computational environment for the analysis. Alternatively, if you are using Python, this environment.yml file contains a specification of the software environment required to run the code in the repository.
  • README.md: This file contains information about the repository, including a brief description of the project, instructions for running the code, and any other relevant information.

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