# Comprehensive and Robust Tools for Analysis of Tumor Heterogeneity and Evolution

> **NIH NIH U24** · PRINCETON UNIVERSITY · 2022 · $788,098

## Abstract

Project Summary/Abstract
In recent years, precision medicine approaches based on molecular changes in an individual patient’s
tumor have become a promising strategy for diagnosis and treatment of cancer. These approaches are
challenged by the fact that tumors are a heterogeneous collection of cells that change over time and in
response to treatment. At the DNA sequence level, changes range in scale from single-nucleotide
mutations to large chromosomal rearrangements and whole-genome duplications. New DNA/RNA
sequencing technologies enable measurement of this heterogeneity and provide data to infer the
evolutionary history of a tumor. However, the algorithms and software necessary to analyze the
complexities of tumor heterogeneity and evolution remain limited in scope. We propose to develop a
comprehensive software toolkit to analyze tumor heterogeneity and tumor evolution across space, time,
and genomic scale. This toolkit will be based on advanced combinatorial and statistical algorithms
developed by PI over the past several years. These algorithms will be unified into a robust,
computationally efficient, and statistically sound software package. This toolkit will incorporate modules
for different types of tumor samples including single tumor samples, multiple tumor regions, multiple
anatomical sites (e.g. primary tumor and metastasis), and multiple time points. The software will also
analyze data from different sequencing approaches (whole-genome, whole-exome, and targeted
sequencing) and different sequencing technologies including bulk tumor, single-cell, short-read, and
long-read. The software package will be open source and will be released to run on individual computers,
computing clusters, or in cloud computing environments. Extensive documentation and training will be
provided to facilitate use by a wide range of users from expert bioinformaticians to clinicians. These
powerful data analytic tools will enable researchers to characterize the heterogeneity within tumors with
high accuracy, enabling greater precision in cancer diagnosis and treatment.

## Key facts

- **NIH application ID:** 10476487
- **Project number:** 5U24CA248453-03
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Benjamin Raphael
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $788,098
- **Award type:** 5
- **Project period:** 2020-09-24 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10476487

## Citation

> US National Institutes of Health, RePORTER application 10476487, Comprehensive and Robust Tools for Analysis of Tumor Heterogeneity and Evolution (5U24CA248453-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10476487. Licensed CC0.

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