# Data Analysis Unit

> **NIH NIH U2C** · CHILDREN'S HOSP OF PHILADELPHIA · 2020 · $419,475

## Abstract

Abstract
Reproducible and robust computational methods, coupled with rigorous statistical
analyses, are critical for the success of CPTCA. We will ensure a unified approach to
data analysis, integration, and management that leverages the existing infrastructure
and the computational strengths of our investigators. Our data analysis effort will be
divided into four tiers, with increasing level of data integration as we move up the tiers.
Methods used in tier one analyses are mostly open-source and developed by other
groups whereas most methods used in tiers two to four analyses will be developed by
our team. Specifically, the integration and visualization of longitudinal multiomics data
poses many new challenges. Members of the Data Analysis Unit (DAU) have extensive
experience in statistics, algorithm development, genomic data analyses, large-scale data
management, and coordination of data analytic efforts within multi-project centers. We
propose the following five specific aims to achieve the goals of the DAU:
1) To design and implement a pipeline for tier-one analyses using both public and in-
house software tools. The pipeline will handle raw data generated using all assay types
by the CPTCA; 2) To develop and deploy computational methods for tier-two analyses.
These methods will be used for the discovery and taxonomy of different cell types in a
tumor, inference of clonal evolution of malignant cells, and inference of spatial
distribution of cells and gene expression patterns in a tumor; 3) To develop network-
based methods for tier-three analyses. These methods will be used for the discovery of
pathways contributing to spatial and temporal heterogeneity of the tumor; 4) To construct
integrated tumor atlases. We will aggregate clinical, genomic and imaging data and
metadata collected throughout the project; 5) To collaborate with the Data Coordinating
Center (DCC) and other research centers of the Human Tumor Atlas Network (HTAN).
Working with investigators at the DCC and other research centers, we will contribute to
benchmarking of software generated by HTAN investigators, development of common
data formats, and improvement of interoperability of software tools.

## Key facts

- **NIH application ID:** 10016229
- **Project number:** 5U2CCA233285-03
- **Recipient organization:** CHILDREN'S HOSP OF PHILADELPHIA
- **Principal Investigator:** Kai Tan
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $419,475
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10016229

## Citation

> US National Institutes of Health, RePORTER application 10016229, Data Analysis Unit (5U2CCA233285-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10016229. Licensed CC0.

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