Alzheimer's clinical research data via R packages: The alzverse
Michael C. Donohue, Kedir Hussen, Oliver Langford, Richard Gallardo, Gustavo Jimenez‐Maggiora, Paul S. Aisen

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.
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…
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Taxonomy
TopicsDementia and Cognitive Impairment Research · Alzheimer's disease research and treatments · Meta-analysis and systematic reviews
