# Alzheimer's clinical research data via R packages: The alzverse

## TL;DR

This paper introduces R packages that provide easy access to curated Alzheimer's disease datasets, improving research transparency and reproducibility.

## Contribution

The novel contribution is the creation of R data packages and the alzverse framework for integrating Alzheimer's datasets with standardized formats.

## Key findings

- A4LEARN and ADNIMERGE2 R packages bundle curated Alzheimer's datasets with documentation and analysis tools.
- The alzverse package unifies these datasets using a common standard for meta-analyses.
- These tools enhance collaboration and reproducibility in Alzheimer's clinical research.

## Abstract

Sharing clinical research data is essential for advancing Alzheimer's disease (AD) research, yet challenges in accessibility, standardization, documentation, usability, and reproducibility persist.

We developed R data packages to streamline access to curated datasets from key AD studies. A4LEARN includes data from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) randomized trial and its companion observational study, the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN). ADNIMERGE2 contains curated data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a longitudinal biomarker and imaging study.

These packages bundle data, documentation, and reproducible analysis vignettes into portable, analysis‐ready formats that can be installed and used within R. We also introduce the alzverse package, which applies a common data standard to integrate study‐specific packages and facilitate meta‐analyses.

By promoting collaboration, transparency, and reproducibility, R data packages provide a scalable framework to accelerate AD clinical research.

R packages enable access to curated Alzheimer's clinical study datasets.A4LEARN and ADNIMERGE2 provide portable, analysis‐ready data resources.R packages integrate data, documentation, and reproducible analysis vignettes.alzverse unifies study packages via common standards to support meta‐analyses.Tools promote transparency, collaboration, and reproducibility in Alzheimer's disease (AD) research

R packages enable access to curated Alzheimer's clinical study datasets.

A4LEARN and ADNIMERGE2 provide portable, analysis‐ready data resources.

R packages integrate data, documentation, and reproducible analysis vignettes.

alzverse unifies study packages via common standards to support meta‐analyses.

Tools promote transparency, collaboration, and reproducibility in Alzheimer's disease (AD) research