# Improving detection and interpretation of clinically relevant structural variation

> **NIH NIH R01** · CHILDREN'S HOSP OF PHILADELPHIA · 2020 · $723,263

## Abstract

Project summary and abstract
Human disease is caused by several different types of structural variation, including deletions, duplications,
and inter and intra chromosomal rearrangements. Currently, no one diagnostic test can identify all of these
changes, which can lead to a diagnostic odyssey with serial genetic testing. Whole genome sequencing (WGS)
allows for the detection of point mutations, small indels and large structural variants (SV) in a single test, and
has the potential to replace both exome sequencing and chromosomal microarrays in the clinical setting.
However, the adoption of clinical testing for SVs from WGS has been hampered by both technical and
interpretative challenges. Existing algorithms for the detection of SVs from WGS suffer from high false-positive
rates, reference bias, and mappability issues. This proposal will address the issues of detection, interpretation,
and reanalysis of copy number and other structural variation in individuals presenting with pediatric genetic
disorders. We will utilize SV data from various types of genomic technologies in order to minimize false
positives, incorporate genomic positional information, and enhance pathogenicity determination by the
prioritization of these variants. In this proposal, we will utilize two orthogonal methodologies, chromosomal
microarray and de novo assembled optical genome maps, to optimize the sensitivity and specificity of SV
detection. Since the number of SVs identified from whole genome data can number into the thousands, the
lack of tools for annotation and interpretation of SVs results in a huge burden for clinical laboratories. We
propose to facilitate the prioritization of clinically-relevant SV by developing web-based analysis tools that
integrate patients’ phenotypes with SV-specific annotations for efficient prioritization and reporting of clinically
relevant SVs. We will apply these tools towards the reanalysis copy number variants of uncertain clinical
significance previously identified in our clinical laboratory. In addition, additional characterization of
duplications of uncertain clinical significance with be investigated using targeted optical maps to determine the
location and orientation of the duplicated region. The impact of new gene discovery on SV interpretation, as
well as additional information regarding insertional locations, will be assessed for their contribution to changes
in classification of SVs.

## Key facts

- **NIH application ID:** 9986001
- **Project number:** 5R01HG009708-04
- **Recipient organization:** CHILDREN'S HOSP OF PHILADELPHIA
- **Principal Investigator:** Laura K Conlin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $723,263
- **Award type:** 5
- **Project period:** 2017-09-05 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986001

## Citation

> US National Institutes of Health, RePORTER application 9986001, Improving detection and interpretation of clinically relevant structural variation (5R01HG009708-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9986001. Licensed CC0.

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