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Creating and sharing reproducible research code the workflowr way.

John D Blischak1, Peter Carbonetto1,2, Matthew Stephens1,3

  • 1Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.

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|November 15, 2019
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Summary
This summary is machine-generated.

The workflowr R package enhances scientific reproducibility and accessibility by integrating version control, literate programming, and automated checks. This workflow simplifies sharing reproducible research and results via a website, benefiting scientists of all backgrounds.

Keywords:
Rinteractive programmingliterate programmingopen sciencereproducibilityversion controlworkflow

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Area of Science:

  • Computational Biology
  • Data Science
  • Scientific Computing

Background:

  • Reproducibility, documentation, and shareability are vital for scientific impact.
  • Achieving these goals requires specialized tools and careful workflow management.
  • Existing tools for reproducibility can have a steep learning curve for many scientists.

Purpose of the Study:

  • To introduce workflowr, an R package designed to simplify reproducible scientific analyses.
  • To provide a standardized workflow for scientists, regardless of their technical background.
  • To enhance the accessibility and shareability of research code, results, and documentation.

Main Methods:

  • Developed the workflowr R package, integrating version control with Git.
  • Incorporated literate programming using R Markdown for dynamic document generation.
  • Implemented automatic checks and safeguards to ensure code reproducibility.
  • Facilitated project sharing through automatically generated browsable websites.

Main Results:

  • Workflowr enables R users to create reproducible projects with accessible results, figures, and development history.
  • Projects are easily shareable with collaborators via a URL, including source code and reproducibility safeguards.
  • The package offers a simple interface, allowing novice users to benefit from advanced reproducibility tools.

Conclusions:

  • Workflowr effectively addresses challenges in scientific reproducibility and documentation.
  • The package promotes a standardized workflow, making scientific analyses more accessible and impactful.
  • Workflowr is an open-source R package available on CRAN, supporting the scientific community.