| 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 |
Publication 9542
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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