ADataViewer

ADataViewer provides exploration and evaluation of patient-level Alzheimer's disease (AD) cohort datasets to support reproducible, data-driven research.

Key Features:

• Dataset exploration: Enables examination of patient-level cohort datasets and variable-level content to identify datasets matching specific research requirements.
• Comprehensive dataset evaluation: Assesses demographics and distributions of AD biomarkers to quantify dataset variability and suitability for comparative studies.
• Ethnoracial diversity analysis: Analyzes ethnoracial composition, including overrepresentation of White/Caucasian individuals, to identify demographic biases.
• Data modality comparison: Compares measured data modalities across cohorts to describe coverage and limitations of available assays and measurements.
• Longitudinal data assessment: Evaluates longitudinal availability of critical AD biomarkers to support temporal analyses of disease progression.

Scientific Applications:

• Facilitating reproducible research: Uses patient-level data assessments to support reproducible and robust analyses in AD research.
• Enhancing comparative studies: Identifies dataset limitations and differences in variables and modalities to guide dataset selection for comparative analyses.
• Promoting diversity in research: Highlights biases in dataset composition to inform inclusion of diverse populations in study design.

Methodology:

Evaluation of nine major clinical cohort studies through direct investigation of patient-level datasets to assess key characteristics and biomarker distributions, analysis of ethnoracial diversity, comparison of measured data modalities across cohorts, and contrast with metadata-based approaches.