Genotype imputation performance of three reference panels using African ancestry individuals

Abstract

Genotype imputation estimates unobserved genotypes from genome-wide makers, to increase genome coverage and power for genome-wide association studies. Imputation has been successful for European ancestry populations in which very large reference panels are available. Smaller subsets of African descent populations are available in 1000 Genomes (1000G), the Consortium on Asthma among African ancestry Populations in the Americas (CAAPA) and the Haplotype Reference Consortium (HRC). We compared the performance of these reference panels when imputing variation in 3747 African Americans (AA) from two cohorts (HCV and COPDGene) genotyped using Illumina Omni microarrays. The haplotypes of 2504 (1000G), 883 (CAAPA) and 32,470 individuals (HRC) were used as reference. We compared the number of variants, imputation quality, imputation accuracy and coverage between panels. In both cohorts, 1000G imputed 1.5-1.6× more variants than CAAPA and 1.2× more than HRC. Similar findings were observed for variants with imputation R > 0.5 and for rare, low-frequency, and common variants. When merging imputed variants of the three panels, the total number was 62-63 M with 20 M overlapping variants imputed by all three panels, and a range of 5-15 M variants imputed exclusively with one of them. For overlapping variants, imputation quality was highest for HRC, followed by 1000G, then CAAPA, and improved as the minor allele frequency increased. 1000G, HRC and CAAPA provided high performance and accuracy for imputation of African American individuals, increasing the number of variants available for subsequent analyses. These panels are complementary and would benefit from the development of an integrated African reference panel.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

“…Genotype imputation, despite being a standard practice in modern genetic association studies, remains challenging in populations of Hispanic/Latino or African ancestry, particularly for rare variants [1][2][3][4][5][6]. One obstacle lies in the lack of appropriate whole genome sequence reference panels for these admixed populations.…”

Evaluating the Accuracy of Imputation Methods in a Five-Way Admixed Population

“…Over the past decade, genotyping technologies for genome-wide association studies (GWAS) have allowed for extensive and rapid genotyping of common variants (Ding and Jin, 2009; Ragoussis, 2009; Vergara et al, 2018). Commercial single nucleotide polymorphism (SNP) genotyping arrays contain between 300 000 and 2.5 million markers, but none have complete coverage of the human genome.…”

“…African and admixed populations are more heterogeneous in their haplotype block structure and, as such, would benefit from a larger reference dataset incorporating more genetic diversity (Vergara et al, 2018). Reference datasets of this nature would increase the chances that an observed haplotype is present in the reference data, thereby greatly improving the imputation accuracy for African and admixed individuals with African ancestry.…”

Multi-ethnic transcriptome-wide association study of prostate cancer

“…Additionally, we performed GWAS across 4.6M SNPs in a nearly 2,200 Japanese American individuals and 7.0M SNPs in 2,147 Latin American individuals. Notably, this GWAS includes imputed SNPs from 1000G and CAAPA, two reference panels not available at the time of the original studies of this cohort [17, 18, 22, 30].…”