# Novel Computation Methods for the Analysis of Cell-Free DNA Sequence Data

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $552,176

## Abstract

Project Summary
Non-invasive detection of cell-free DNA(cfDNA) promises to impact clinical regimens of a wide range of
diseases, e.g. prenatal conditions, cancer, transplantation, autoimmune disease, trauma, and cardiovascular
disease. While this field is emerging as one of the most promising and exciting areas of medicine, few
bioinformatics tools are available to facilitate the information extraction from cfDNA sequencing data, although
cfDNA data possesses many unique properties. In this proposal, we aim to generate a suite of computational
methods facilitating the analysis and interpretation of cfDNA sequencing data, and demonstrate its utilities in
cancer detection and characterization. Specifically, we will develop computational methods for the following
applocations: (1) Ultra-sensitively detect and locate multiple types of cancer using cfDNA methylome; (2) Detect
Copy Number Variation (CNV) in cfDNA sequencing data; (3) Annotate Single Nucleotide Variations (SNV) in
cfDNA sequencing data. These computational tools will be validated with cfDNA samples collected from a cohort
of lung cancer patients participating in an immunotherapy clinical trial, a repository of blood samples from patients
with different types of cancer, and a cohort of liver cancer patients. Although we use cancer as the main context
for developing these applications, many of the methods can be adapted to other diseases, e.g. prenatal diagnosis
and organ transplant monitoring. We expect that the above open-source tools will significantly facilitate cfDNA-
based disease diagnosis and monitoring.
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## Key facts

- **NIH application ID:** 10004012
- **Project number:** 5R01CA246329-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Steven M. Dubinett
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $552,176
- **Award type:** 5
- **Project period:** 2019-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10004012

## Citation

> US National Institutes of Health, RePORTER application 10004012, Novel Computation Methods for the Analysis of Cell-Free DNA Sequence Data (5R01CA246329-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10004012. Licensed CC0.

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