# Data Processing, Analysis and Modeling Unit

> **NIH NIH U2C** · WASHINGTON UNIVERSITY · 2020 · $265,906

## Abstract

Project Summary/Abstract: Data Analysis Unit
The over-arching goal of the Data Analysis Unit for the Washington University Human Tumor Atlas Research
Center (WU-HTARC) is to provide bioinformatics tools and processing/analysis infrastructure for in-depth
analyses of the data generated in the Characterization Unit. Most importantly, we will integrate data across
both the methodological (omics/imaging/phenotypic analyses) and the dimensional (1D/2D/3D/time) spectrums
into coherent and accessible tumor atlases for each of the three cancer types: GBM, PDAC, and BRCA/TNBC.
At the basic level, each atlas will consist of first cataloging a variety of numerically-computed metrics for cell
types, including fractions (1D), density, dispersion, and location measures for individual cell types and
Euclidean measures of spatial interspersedness of different cell types, e.g. immune and tumor cells (2D and
3D), and how these metrics change with time. We will then correlate this information with both genomic
analyses, such as mutation signatures, clonality, and significantly mutated genes/regions/pathways, proteomic
and metabolomics analyses, and image-derived data. The core of the atlas will be a MySQL relational
database that not only stores all collected data, but links them along these different dimensions. Users will
interface with the atlas through a sophisticated viewer/query browser-based web portal that will support both
traditional text-based queries, as well as spatial-based queries (shape, feature locations, etc.). The cohesion
among the three atlases, in terms of the spectrum of data used and the approaches of their construction, will
allow users to generate new types of hypotheses not now possible and to perform pan-cancer analyses to
reveal commonalities and differences in the three representative solid tumors, and to potentially extrapolate
these findings to other tumors.

## Key facts

- **NIH application ID:** 9999543
- **Project number:** 5U2CCA233303-03
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Li Ding
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $265,906
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9999543

## Citation

> US National Institutes of Health, RePORTER application 9999543, Data Processing, Analysis and Modeling Unit (5U2CCA233303-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9999543. Licensed CC0.

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