Identifying impactful rare genetic variants using advanced data integration techniques
Official title: Integrating 4DN data to identify functional rare variants in UDN and GTEx
Funded at Stanford University · NIH-11125138 · Data updated 2026-11-12
This study is looking at how unusual genetic changes can cause rare diseases by using advanced computer techniques to find out which of these changes might affect how genes work, helping us learn more about the genetics behind these conditions.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | June 10, 2025 |
| Project end | May 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $308,800 |
| NIH project number | 1R03OD039976-01 |
| Project ID | NIH-11125138 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with rare genetic diseases or those who have a family history of such conditions.
✕Less likely to help
Patients with common genetic disorders or those without a known genetic component to their condition may not benefit from this research.
What this research studies
This research investigates how rare genetic variants contribute to genetic diseases by integrating various data types, including gene expression and genomic annotations. The approach utilizes a machine learning model called Watershed to prioritize rare variants based on their potential impact on gene expression and 3D genomic structure. By analyzing the relationship between gene expression outliers and genomic architecture, the study aims to uncover rare variants that may be more distantly located from the genes they affect. This innovative methodology could enhance our understanding of the genetic basis of rare diseases.
Why it matters
Potential benefit: If successful, this research could lead to improved identification of rare genetic variants that significantly contribute to genetic diseases, potentially guiding more effective treatments.
How similar studies have gone: Previous research has shown promise in using integrated genomic and transcriptomic approaches to identify impactful genetic variants, suggesting that this methodology could yield significant insights.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Montgomery, Stephen — Stanford University
- Study coordinator: Montgomery, Stephen
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.