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An example of how to organize files for a research project to increase reproducibility

Python 12.70% Jupyter Notebook 33.01% Dockerfile 54.29%

project_template's Introduction

Project template

Project template for setting up a directory and file structure for a new research project. The intended contents of each directory is explained in separate README.md files.

Overview

project
|- doc/                documentation for the study
|
|- data/               raw and primary data, essentially all input files, never edit!
|  |- raw_external/
|  |- raw_internal/
|  |- meta/
|
|- code/               all code needed to go from input files to final results
|- notebooks/
|
|- intermediate/       output files from different analysis steps, can be deleted
|- scratch/            temporary files that can be safely deleted or lost
|- logs/               logs from the different analysis steps
|
|- results/            output from workflows and analyses
|  |- figures/
|  |- tables/
|  |- reports/
|
|- .gitignore          sets which parts of the repository that should be git tracked
|- Snakefile           project workflow, carries out analysis contained in code/
|- config.yml          configuration of the project workflow
|- environment.yml     software dependencies list, used to create a project environment
|- Dockerfile          recipe to create a project container

project_template's People

Contributors

rasmusagren avatar varemo avatar

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