veera927
ADaM-R-Programming
A repository for developing CDISC ADaM datasets in R using the Admiral package, covering multiple domains with modular programming and SAS output quality control.
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FR-AI / ANALYSISWhy it is worth attention
It provides ready-to-run, self-contained R scripts for 20 high-impact figure types (e.g., Manhattan, Circos, Sankey, raincloud) that are notoriously hard to code from scratch, making it a practical reference for researchers aiming to produce publication-quality graphics.
Who it is for
- Academic researchers in life sciences or bioinformatics
- R users who need to create complex publication figures
- Data visualization instructors looking for reproducible examples
- Data scientists wanting to learn advanced ggplot2 techniques
Use cases
- Replicating a figure style from a specific journal paper for your own data
- Learning how to build non-trivial ggplot2 plots (raincloud, heatmap, Sankey) step by step
- Quickly generating example figures for a manuscript or presentation without downloading external data
- Teaching R and ggplot2 with reproducible, self-contained case studies
Strengths
- Fully self-contained with no external data dependencies; runs on a fresh clone
- Covers 20 distinct figure types, each accompanied by a data simulator and a plot script
- All cases share a unified theme and are runnable with a single command via run_all.R
- MIT license allows free reuse and modification of all code
Considerations
- Heavy dependency on many R packages, including an archived build (gghalves), which may cause installation issues
- Simulated data is intentionally minimal and may require column-name mapping before swapping in real data
- No automated testing or continuous integration is mentioned, so robustness across R versions is unverified
README quick start
Quick start
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