Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power
- 1 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Genetics
- Vol. 53 (2), 195-+
- https://doi.org/10.1038/s41588-020-00766-y
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.Funding Information
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (K01MH121659, T32MH017119)
- Heiwa Nakajima Foundation
- Masason Foundation
- Fundação de Amparo à Pesquisa do Estado de São Paulo (#2018/09328-2)
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Agency for Medical Research and Development
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