# Data Analysis Core

> **NIH NIH U54** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2021 · $401,693

## Abstract

DATA ANALYSIS CORE (DAC): PROJECT SUMMARY
To characterize signatures of senescence and their functional implications in multiple human tissues across
the life span, the Columbia University Senescence Tissue Mapping (CUSTMAP) Center proposes a novel
combination of genome-wide and targeted molecular panels to map cellular composition with spatial context.
The Data Analysis Core correspondingly plays a key role in all aspects of data processing and analysis,
tissue mapping, and identification of markers of senscence, as well as data harmonization, coordination, and
dissemination through the SenNet Consortium Data Coordination Center (CODCC). To achieve these goals,
the DAC will use an integrative analysis approach to combine multi-modal data consisting of transcriptome-
wide and targeted proteomics profiling in the tissues being examined across the adult human lifespan. This
includes the three major data modalities described in the Biological Analysis Core: large-scale high-resolution
Iterative Indirect Immunofluorescence Imaging (4i) data, genome-wide spatially resolved Spatial
Transcriptomics (ST) data, and transcriptome-wide single-nucleus RNA-seq data. These three data
modalities in concert allow for comprehensive (genome-wide) molecular characterization at single-cell
resolution in space; this combination of attributes has not been demonstrated by any single experimental
technique at scale currently in human tissue. By integrating these modalities using established processing
and analysis workflows, the Data Analysis Core will generate maps of known and novel senescence-
associated markers, senescent cells, and the effects of senescent cells on their surroundings in each tissue
type. To achieve these goals, the Data Analysis Core will implement modality-specific data processing
workflows, followed by cross-modal data analysis, cross-individual map-building, and identification of novel,
cell type-specific senescence signatures in brain, spinal cord, and skin. This includes cross-referencing
tissue-based signatures to data from ongoing efforts to identify senescence-related signatures in
cerebrospinal fluid and blood, the primary biofluids associated with central nervous system and skin. Finally,
the Data Analysis Core will work closely with the Administrative Core to interface with the SenNet CODCC,
in order to harmonize all aspects of data management and analysis with other members of the consortium.

## Key facts

- **NIH application ID:** 10385187
- **Project number:** 1U54AG076040-01
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Vilas Menon
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $401,693
- **Award type:** 1
- **Project period:** 2021-09-30 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10385187

## Citation

> US National Institutes of Health, RePORTER application 10385187, Data Analysis Core (1U54AG076040-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10385187. Licensed CC0.

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