# Data Core

> **NIH NIH U19** · UNIVERSITY OF TEXAS DALLAS · 2024 · $255,790

## Abstract

This proposal aims to realize the vision of a “molecular encyclopedia” of pain-associated genes and cell types in
the human dorsal root ganglia (hDRG), peripheral nerve, and spinal cord. The mission is to build data
infrastructure and provide computational research support that will be needed for us to achieve our Center’s
research goals and to effectively make our data accessible to all our cores, other PRECISE Centers and the
broader community. This will facilitate discovery for diverse types of researchers. The first aim will be for the
Core to provide standardized workflows for the creation and management of the raw data (including sequencing,
tissue imaging, and functional datasets), along with associated metadata, and processed data. We will work
closely with the Tissue Procurement and Processing Core to maintain records and de-identified metadata around
the tissues collected and the data that will be generated. The second aim will be to create standardized workflows
and pipelines to process bulk, single-cell/nucleus, and spatial RNA-seq (and associated ribosome footprinting
and ATAC-seq) that will perform quality control (following ENCODE and GTEx standards), identify different cell
types, their gene markers, and differentially expressed genes for clinical phenotype and demographics-based
cohorts (from human DRGs, peripheral nerves, and spinal cords). Finally, the Core will develop algorithms
(provided as software tools and scripts) to retrieve specific information and test specific hypotheses from different
datasets in conjunction with each research project and to meet the scientific milestones of this grant. We will
also develop tools to analyze data from multiple assays in our Research Projects, as well as from other PRECISE
Centers in an integrative fashion. The work conducted in this Core will allow us to meet the proposed goals of
this Center and fully characterize peripheral and spinal pain pathways across different tissues, chronic pain
conditions, age, and sex. Our impact will also go beyond our Center as we plan to make our data and pipelines
accessible to other researchers, facilitating collaborations, and integration of other datasets.

## Key facts

- **NIH application ID:** 10930064
- **Project number:** 5U19NS130608-03
- **Recipient organization:** UNIVERSITY OF TEXAS DALLAS
- **Principal Investigator:** Diana Tavares Ferreira
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $255,790
- **Award type:** 5
- **Project period:** 2022-09-19 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10930064

## Citation

> US National Institutes of Health, RePORTER application 10930064, Data Core (5U19NS130608-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10930064. Licensed CC0.

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