Estimating how protein-changing gene variants affect traits and disease
Bayesian estimation of gene effects on traits from coding variants
This project builds new methods that use rare protein-changing gene variants to estimate how much each gene influences human traits and diseases, which could help people with genetic conditions.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11332536 on NIH RePORTER |
What this research studies
Researchers will analyze large human genetic datasets to use rare protein-coding changes — including loss-of-function mutations, deletions, and duplications — to estimate each gene's effect on a trait. Because tests at single genes are often underpowered, they will share information among similar genes using a machine-learning method called GeneBayes within a hierarchical Bayesian framework. The team will develop open-source software and release summary statistics so other scientists and clinicians can apply the methods. The work is primarily computational and relies on existing genomic data rather than routine clinic visits.
Who could benefit from this research
Good fit: People with sequenced genomes or exomes, or patients represented in large genetic research datasets, are the most relevant candidates to benefit from this work.
Not a fit: People whose conditions are not driven by rare coding variants or who do not have genomic data are unlikely to receive direct benefit.
Why it matters
Potential benefit: If successful, this could help pinpoint genes that drive disease and guide better diagnostics and new targets for treatments.
How similar studies have performed: Previous GWAS and rare-variant burden tests have had success finding disease-associated genes and GeneBayes builds on promising prior methods, but this specific Bayesian hierarchical extension is novel.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Pritchard, Jonathan K — Stanford University
- Study coordinator: Pritchard, Jonathan K
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.