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Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Genotype imputation for African Americans using data from HapMap phase II versus 1000 genomes projects.
Yun J Sung1, C Charles Gu, Hemant K Tiwari
1Division of Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, Missouri 63110-1093, USA. yunju@wubios.wustl.edu
Genetic Epidemiology
|May 31, 2012
Summary
Genotype imputation for African Americans is improved using the 1000 Genomes Project reference panel, offering more variants and better accuracy, especially with the union strategy.
Area of Science:
- Genetics
- Bioinformatics
- Population Genetics
Background:
- Genotype imputation enhances statistical power and cross-study comparisons by inferring untyped single nucleotide polymorphisms (SNPs) using reference panels.
- Imputing genotypes in African American populations is complex due to shorter linkage disequilibrium blocks and admixed ancestry, lacking ideal reference panels.
- The 1000 Genomes (1KG) Project is increasingly utilized for genotype imputation, necessitating evaluation against established panels like HapMap.
Purpose of the Study:
- To evaluate three genotype imputation strategies (intersection, union, merge) for African Americans.
- To compare imputation performance using the 1000 Genomes (1KG) Project versus HapMap reference panels.
- To assess imputation accuracy and variant yield across different minor allele frequency (MAF) spectra.
Main Methods:
- Evaluated three imputation strategies: intersection (SNPs in both CEU and YRI), union (SNPs in either CEU or YRI), and merge (combined results from separate CEU and YRI imputations).
- Utilized 1KG and HapMap reference panels for imputation.
- Analyzed 23,707 SNPs on chromosomes 21 and 22 from 1,075 African American HyperGEN samples genotyped on Affymetrix SNP Array 6.0.
Main Results:
- 1KG-based imputations yielded significantly more variants (3x common, 8x rare/low-frequency) compared to HapMap-based imputations.
- 1KG imputation accuracy was slightly lower pre-filtering but higher post-filtering than HapMap.
- The union strategy offered the highest variant yield with good accuracy, while intersection provided the highest accuracy but lowest yield. Merge strategy showed the lowest accuracy.
Conclusions:
- 1KG-based genotype imputation substantially increases variant discovery across the MAF spectrum for African Americans.
- The union strategy with 1KG data is recommended for maximizing imputation yield and accuracy in this population.
- Ongoing 1KG Project updates are expected to further improve imputation performance for diverse populations.
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