Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power.
Atkinson EG, Maihofer AX, Kanai M et al.
Publication Details
Comprehensive information about this research publication
Abstract
Summary of the research findings
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.
4,309 admixed African European ancestry individuals
Study Statistics
Key metrics and study information
Analysis
Comprehensive review of health and genetic findings
Important Disclaimer: This review has been performed semi-automatically and is provided for informational purposes only. While we strive for accuracy, this analysis may contain errors, omissions, or misinterpretations of the original research. DNA Genics disclaims all liability for any inaccuracies, errors, or consequences arising from the use of this information. Users should independently verify all information and consult original research publications before making any decisions based on this content. This analysis is not intended as a substitute for professional scientific review or medical advice.
Analysis In Progress
Our analysis of this publication is currently being prepared. Please check back soon for comprehensive insights into the health and genetic findings discussed in this research.