# Computational methods for detecting patterns of complex genomic variation

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $241,277

## Abstract

Project Summary
Rearrangements of genomic segments or structural variation (SVs), include changes (increase/decrease)
of copy number, inversions, translocations, and other mechanisms that change or rearrange the DNA
content of a cell. Complex SVs can mediate many constitutional diseases; highly pathological germline
rearrangements can damage the viability of the embryo; and somatic rearrangements can increase the
pathology of many diseases, including cancer.
 The genomic footprint of complex SVs is a changed karyotype, defined by a collection of sequences of
oriented genomic intervals whose coordinates are drawn from a reference genome, so that every sequence
corresponds to a haploid or marker chromosome. The goal of this renewal proposal is to develop tools to
elucidate the karyotype of a donor. In Aim 1, we will develop methods to reconstruct focal amplifications
using long-read technology. In Aim 2, we will develop methods to elucidate genome scale karyotypes for
constitutional disorders using optical genome maps. Highly rearranged regions will be clarified using a mix
of experiments and computation in Aim 3. Finally, in Aim 4, we will extend the notion of a karyotype to
predict the 3-dimensional conformation of ecDNA using Hi-C. The development of our aims will require
novel graph theoretic and combinatorial optimization methods applied to new sequencing technologies.
Their successful implementation will provide novel algorithms and software tools for improved karyotyping,
deeper insights into gene regulation and DNA repair for focal amplifications, and better understanding of
disease pathology mediated by complex variations.

## Key facts

- **NIH application ID:** 10980957
- **Project number:** 2R01GM114362-09
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Vineet Bafna
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $241,277
- **Award type:** 2
- **Project period:** 2016-01-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10980957

## Citation

> US National Institutes of Health, RePORTER application 10980957, Computational methods for detecting patterns of complex genomic variation (2R01GM114362-09). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10980957. Licensed CC0.

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