Related Experiment Video
Updated: Jun 14, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
Alzheimer's clinical research data via R packages: The alzverse
Michael C Donohue1, Kedir Hussen1, Oliver Langford1
1Epstein Family Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA.
Introduction:
Sharing clinical research data is essential for advancing Alzheimer's disease (AD) research, yet challenges in accessibility, standardization, documentation, usability, and reproducibility persist.
Methods:
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.
Results:
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.
Discussion:
By promoting collaboration, transparency, and reproducibility, R data packages provide a scalable framework to accelerate AD clinical research.
Highlights:
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.
More Related Videos
08:43Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
09:47DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
Related Concept Videos
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Alzheimer's Disease: Treatment
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Statistical Software for Data Analysis and Clinical Trials
Alzheimer Disease l: Introduction
Alzheimer Disease ll: Pathophysiology