PARIST-Trial Workflow • Severe-Malaria AKI Project

End-to-end, reproducible code + text for the manuscript
“Paracetamol for Renal Recovery in Severe Malaria (PARIST Trial)”

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📑 Table of contents

1. Project scope
2. Folder structure
3. Quick-start
4. Re-running the full pipeline
5. Continuous integration
6. Authorship & contributions
7. Data governance
8. License & citation
9. Contact

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Project scope

This repository is the single source of truth for:

• De-identified analysis datasets
• R scripts and R Markdown notebooks
• Auto-generated figures & tables
• The manuscript in markdown/LaTeX (rendered to PDF & HTML)
• GitHub Actions CI to guarantee that analyses and rendering are repeatable

Why a public workflow?
Releasing code and de-identified data (+ exact package versions via renv) fulfils FAIR-data principles, improves transparency, and accelerates follow-up research.

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Folder structure

parist-trial-workflow/
├── analysis/          # R scripts & notebooks
│   ├── 01\_data-cleaning.R
│   ├── 02\_descriptive.Rmd
│   ├── 03\_RMST\_analysis.R        <- primary analysis
│   └── utils/plot\_theme.R
├── data/
│   ├── raw/            # 🔒 not in git (see .gitignore)
│   └── derived/        # de-identified CSVs shared openly
├── manuscript/
│   ├── PARIST\_manuscript.Rmd
│   ├── references.bib
│   └── journal-template.tex
├── figures/            # auto-generated PNG/PDF/SVG
├── docs/               # rendered manuscript (CI artifact / GitHub Pages)
├── archive/            # original Word files & approvals
├── .github/workflows/ci.yml
├── renv.lock           # pinned R package versions
├── LICENSE  |  CITATION.cff
└── README.md           # you are here

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Quick-start

Clone and recreate the R environment

git clone https://github.com/<ORG>/parist-trial-workflow.git
cd parist-trial-workflow

# one-liner to restore exact packages
R -q -e "install.packages('renv'); renv::restore()"

Run the primary analysis

Rscript analysis/03_RMST_analysis.R

Render the manuscript locally

R -q -e "rmarkdown::render('manuscript/PARIST_manuscript.Rmd',
                           output_dir = 'docs')"
open docs/PARIST_manuscript.pdf

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Re-running the full pipeline

Stage	Script / tool	Output
1 Import & clean	01_data-cleaning.R	data/derived/parist_analysis_set.csv
2 Descriptive stats	02_descriptive.Rmd	figures/Table1.png
3 Primary RMST + adjusted models	03_RMST_analysis.R	figures/Fig2_RMST_curve.pdf, analysis/results/rmst_summary.csv

The CI workflow executes exactly these steps on every push / PR to guarantee reproducibility.

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Continuous integration

.github/workflows/ci.yml:

1. Checks out the repo.
2. Restores the renv cache.
3. Runs analysis scripts; fails if any exit non-zero.
4. Renders the manuscript to PDF.
5. Uploads artifacts & (optionally) deploys docs/ to GitHub Pages.

Status badge at the top of this README shows the latest build.

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Authorship & contributions

We adopt the CRediT taxonomy. Example (edit as needed):

Author	Contribution(s)
A.B.	Conceptualization, Methodology, Writing – original draft
C.D.	Formal analysis, Software, Visualization
E.F.	Investigation, Data curation
G.H.	Supervision, Funding acquisition

➡️ How to contribute:

1. Create a feature branch: git checkout -b feat/<slug>
2. Commit with Conventional Commit prefix (feat:, fix:, docs:…)
3. Open a Pull Request; CI must be green & 2 reviews obtained.
4. Squash-merge to main.

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Data governance

Data tier	Location	Policy
Raw identifiable	Institution file-share only	Never pushed to GitHub
Derived de-identified	data/derived/	Commit OK; shared under CC-BY 4.0
Post-acceptance	Zenodo / Mendeley Data	DOI back-linked here

Corresponding author stores the encryption key for raw ↔︎ derived mapping.

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License & citation

• Code: MIT License – see LICENSE.
• Text & figures: Creative Commons CC-BY 4.0.

A ready-made CITATION.cff lets GitHub generate a citation snippet. When citing, please use the DOI badge at the top of this README once minted.

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Contact

Corresponding author: Dr Paasi George – [georgepaasi8@gmail.com)

For issues or feature requests open a GitHub Issue or start a Discussion.

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Happy analysing – and thanks for advancing open, reproducible clinical science!