Predicting and prioritizing effects of changes in the human genome
Design, prediction, and prioritization of systematic perturbations of the human genome
This project builds computer tools to predict which noncoding DNA changes affect gene control so patients with genetic conditions may get clearer explanations of their genome results.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project ID | NIH-11115715 on NIH RePORTER |
What this research studies
From a patient's point of view, researchers are combining experimental data that deliberately change DNA or its regulation with advanced statistical and machine-learning methods to learn which noncoding variants alter gene activity. They will create software and catalogs that rank and prioritize those variants across many cell types to help point clinicians and scientists toward the most important changes. The work ties together multiple laboratory assays and large genomic datasets so findings can be generalized to untested variants. Ultimately the tools will be shared so others can use them to interpret whole-genome sequencing results.
Who could benefit from this research
Good fit: People with undiagnosed or suspected genetic conditions, individuals who have whole-genome sequencing data, or those willing to donate samples or clinical data would be most relevant to this work.
Not a fit: Patients whose conditions have no genetic basis or who only had limited genetic testing (not whole-genome data) may not see direct benefit from this project.
Why it matters
Potential benefit: If successful, the tools could make it easier to interpret whole-genome sequencing by flagging noncoding changes likely to affect health.
How similar studies have performed: Previous computational and experimental studies have shown promise in predicting noncoding variant effects, but fully accurate and general tools remain limited and this project aims to advance that capability.
Where this research is happening
Durham, United States
- Duke University — Durham, United States (Active)
Researchers
- Principal investigator: Allen, Andrew S — Duke University
- Study coordinator: Allen, Andrew S
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.