# Data Processing, Analysis and Modeling Unit

> **NIH NIH U2C** · OREGON HEALTH & SCIENCE UNIVERSITY · 2021 · $663,501

## Abstract

ABSTRACT – Data Analysis Unit
We propose to create a Data Analysis Unit in service of the Omics and Multidimensional Spatial (OMS) Atlas.
The OMS Atlas will enable discovery of mechanisms of resistance that arise in individual patients with
metastatic breast and prostate cancer during treatment with current generation of targeted therapeutic
combinations and immune checkpoint inhibitors. Treatment will these therapies in metastatic cancer is rarely
effective for an extended period of time, and understanding the mechanisms by which these cancers become
resistant to therapy is the primary goal of the OMS Atlas. The Data Analysis Unit will support this goal by
developing and deploying data management, processing, analysis, and visualization methods and software to
create the Atlas. The OMS Atlas will collect two biopsies, one before treatment and one during treatment for 3
different cohorts of cancer patients. The final product of the Data Analysis Unit will be a complete tumor atlas
accessible via an interactive portal that enables use-case biologists in the OMS Atlas, the HTAN and the larger
research community to develop hypotheses about tumor resistance mechanisms through quantified,
longitudinal, and spatially-resolved comparisons of pre- and on/post-treatment biopsies from individual
patients. Using primary data generated from omics and imaging assays (Tier 1 data), the Data Analysis Unit
will generate three additional tiers of data: (Tier 2) single gene/cell measurements obtained by processing data
from a single data platform; (Tier 3) tumor maps generated by combining single-cell and spatially-resolved
omics and imaging data as well as quantification of systems-level functions such as biological pathway activity
and the cells comprising the tumor and its surrounding tissue using integrative analyses of multiple data
platforms; (Tier 4) a tumor atlas that can be used to compare pre- and on/post-treatment biopsies and identify
features potentially correlated with resistance to treatment. Data tiers will be generated using a robust software
pipeline consisting of a data management system, image management software, a workflow execution system,
and visualization tools. Standardized and reproducible workflows that run on this platform will be implemented
to generate all tiers of data. Statistical and machine learning approaches will be used to create tumor maps by
connecting mirror image sections and cell populations across different assays. The OMS Atlas portal will
provide a single interface with access to 10 different visualizations of tumor maps. Tumor maps can be
visualized and compared longitudinally within a single patient or laterally across patients. Many visualizations
can be displayed simultaneously using a dashboard approach where visualizations can be progressively added
as desired, making it possible to view many different types of data about tumor maps simultaneously.
Specialized animation approaches and 3D techniques will be used i...

## Key facts

- **NIH application ID:** 10246897
- **Project number:** 5U2CCA233280-04
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** Jeremy Goecks
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $663,501
- **Award type:** 5
- **Project period:** 2018-09-19 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246897

## Citation

> US National Institutes of Health, RePORTER application 10246897, Data Processing, Analysis and Modeling Unit (5U2CCA233280-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10246897. Licensed CC0.

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