Identifying impactful rare genetic variants using advanced data integration techniques
Integrating 4DN data to identify functional rare variants in UDN and GTEx
['FUNDING_R03'] · STANFORD UNIVERSITY · NIH-11125138
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
| Phase | ['FUNDING_R03'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | STANFORD UNIVERSITY (nih funded) |
| Locations | 1 site (STANFORD, UNITED STATES) |
| Trial ID | NIH-11125138 on ClinicalTrials.gov |
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.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals with rare genetic diseases or those who have a family history of such conditions.
Not a fit: Patients with common genetic disorders or those without a known genetic component to their condition may not benefit from this research.
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 performed: 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, UNITED STATES
- STANFORD UNIVERSITY — STANFORD, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: MONTGOMERY, STEPHEN — STANFORD UNIVERSITY
- Study coordinator: MONTGOMERY, STEPHEN
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 below.