| Title: | Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power |
| Journal: | Nature Genetics |
| Published: | 18 Jan 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33462486/ |
| DOI: | https://doi.org/10.1038/s41588-020-00766-y |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867648 |
| Citations: | 150 (82 in last 2 years) as of 8 Aug 2024 |
Publication 9542
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.</p>
14 Authors
- Elizabeth G. Atkinson
- Adam X. Maihofer
- Masahiro Kanai
- Alicia R. Martin
- Konrad J. Karczewski
- Marcos L. Santoro
- Jacob C. Ulirsch
- Yoichiro Kamatani
- Yukinori Okada
- Hilary K. Finucane
- Karestan C. Koenen
- Caroline M. Nievergelt
- Mark J. Daly
- Benjamin M. Neale
1 Application
| Application ID | Title |
|---|---|
| 31063 | Methodological extensions to estimate genetic heritability and shared risk factors for phenotypes of the UK Biobank |
Enabling scientific discoveries that improve human health