RNAAgeCalc

RNAAgeCalc computes transcriptional age from tiling array and gene expression data as an R package to quantify aging across multiple tissues and within specific tissue types.

Key Features:

• Implementation: Implemented as an R package that leverages correlation structures among probe measurements from tiling array data.
• Across-Tissue and Tissue-Specific Calculations: Provides both across-tissue transcriptional age calculations and tissue-specific predictions.
• Identification of Age-Related Genes: Uses GTEx-based meta-analysis to identify 1,616 common age-related genes and performs differential expression analyses to detect tissue-specific age-related genes.
• Performance and Validation: Demonstrates superior performance relative to prior age-related gene signatures and shows significant correlation with mutation burden, mortality risk, and cancer stage when applied to TCGA data.

Scientific Applications:

• Transcriptional Age Acceleration: Quantifies transcriptional age acceleration within tissues for studies of biological aging.
• Aging-Related Disease Research: Enables investigation of aging-related diseases, including cancer, by linking transcriptional age with disease-associated molecular changes.
• Clinical Outcome Correlation: Facilitates correlation of transcriptional age metrics with clinical outcomes such as mutation burden, mortality risk, and cancer stage using TCGA data.

Methodology:

Leverages correlation structures among probe measurements from tiling array data, performs meta-analysis on GTEx to identify 1,616 common age-related genes, and conducts differential expression analyses on individual tissues; implemented as an R package.