The Front Page of TranslAGE
Explore the datasets and biomarkers that power TranslAGE
TranslAGE Data Explorer
Browse 180+ datasets and aging biomarkers
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Methodology Overview
Our approach to dataset harmonization
Dataset Harmonization Pipeline
Step 1: Data Curation
Compile DNA methylation data from public and private repositories.
- • 180+ harmonized datasets
- • Standardized metadata
- • Quality control measures
Step 2: Clock Calculation
Calculate 1800+ epigenetic biomarkers using our open-source methylCIPHER package.
- • Chronological clocks
- • Mortality clocks
- • Biomarker panels
Step 3: Age Residualization
Regress out chronological age for comparative analysis.
- • Age-adjusted residuals
- • Cross-dataset comparability
- • Biological age acceleration
Step 4: Analysis Branches
Direct biomarker scores to three key performance domains.
- • Prognostic analysis
- • Responsiveness assessment
- • Stability evaluation
Key Features
Allowing unprecedented cross-study comparison
User-driven analysis with real-time filtering
Freely available for the aging research community
Methodology Overview
Our approach to dataset harmonization and biomarker calculation
Dataset Harmonization Pipeline
Step 1: Data Curation
We compile whole blood DNA methylation data from public and private repositories including GEO, EMBL, and TruDiagnostic.
- • 180 datasets and growing
- • Standardized metadata formatting for cross-study communication
- • Systematic quality control steps
Step 2: Clock Calculation
Calculate 1803 epigenetic biomarkers using our open-source methylCIPHER package.
- • Whole body clocks, trained on chronological age or mortality
- • System-specific scores, such as Systems Age
- • Epigenetic Biomarker Proxies for other omics and clinical biomarkers
Step 3: Age Residualization
Regress out chronological age and sex from every biomarker for each dataset to determine biological age residual.
- • Age-adjusted residuals
- • Cross-dataset comparability
- • Biological age acceleration
Step 4: Analysis Branches
Send biological age residual to three key performance domains for systematic biomarker evaluation.
- • Prognostic pipelines
- • Responsiveness pipelines
- • Stability pipelines
Open Source Tool: methylCIPHER
All epigenetic biomarkers in TranslAGE are calculated using methylCIPHER, our open-source R package for comprehensive epigenetic clock calculation and analysis.
View on GitHubTL;DR:
Allowing unprecedented cross-study comparison
User-driven analysis with real-time filtering and visualization
Freely available resource for the aging research community
Explore Specific Domains
Dive deeper into epigenetic clock performance
Explore S.T.A.R. Domains
Dive deeper into the four performance domains of epigenetic clock validation