Inclusion of Population-specific Reference Panel from India to the 1000 Genomes Phase 3 Panel Improves Imputation Accuracy

Abstract

Imputation is a computational method based on the principle of haplotype sharing allowing enrichment of genome-wide association study datasets. It depends on the haplotype structure of the population and density of the genotype data. The 1000 Genomes Project led to the generation of imputation reference panels which have been used globally. However, recent studies have shown that population-specific panels provide better enrichment of genome-wide variants. We compared the imputation accuracy using 1000 Genomes phase 3 reference panel and a panel generated from genome-wide data on 407 individuals from Western India (WIP). The concordance of imputed variants was cross-checked with next-generation re-sequencing data on a subset of genomic regions. Further, using the genome-wide data from 1880 individuals, we demonstrate that WIP works better than the 1000 Genomes phase 3 panel and when merged with it, significantly improves the imputation accuracy throughout the minor allele frequency range. We also show that imputation using only South Asian component of the 1000 Genomes phase 3 panel works as good as the merged panel, making it computationally less intensive job. Thus, our study stresses that imputation accuracy using 1000 Genomes phase 3 panel can be further improved by including population-specific reference panels from South Asia.

Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese

“…We find that the TWB panel provides a modest, but consistent, improvement in imputation accuracy over the EAS panel, and that the TWB + EAS panel provides a very small improvement over the TWB panel. These results are consistent with previous studies showing that imputation accuracy depends on both sample size and genetic similarity between reference panel and genomes to be imputed 3 , 10 – 12 . We also find an improvement in imputation accuracy when the reference panel is fixed but the SNP array used varies between the custom TWBv2 array (described below) and the commonly used Illumina GSAv2 array (Supplementary Fig.…”

Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

“…Matching alleles and allele frequencies in the study cohort with reference panels as part of pre-imputation QC also relies on us-ing reference data from a matched ancestral background. Reference panels with better coverage of haplotypes from the population of the genotyped cohort will yield a greater number of well-imputed variants for GWASs, especially among lower-frequency variants (Ahmad et al, 2017;Howie et al, 2012). Table 1 lists major imputation panels that are currently publicly available.…”

“…Current imputation methods are summarized in Supplemental Methods III. Joint imputation using the largest applicable reference panel is expected to perform at least as well as subsetting that reference panel to match the target population (Ahmad et al, 2017;Howie et al, 2012), possibly due to maintaining a larger sample size for phasing. Use of the same reference panel for all cohorts also avoids potential confounding with varying imputation quality.…”

EPIGEN-Brazil Initiative resources: a Latin American imputation panel and the Scientific Workflow

“…In addition to the 1092 individuals from Phase 1, Phase 3 of the 1KGP panel has incorporated 1412 new individuals, including four new populations from Africa, one from admixed Latin America, two from East Asia, and five from South Asia, each with 61-113 individuals (Supplemental Table S3; Supplemental Material Section 2.2.2). Notwithstanding this improvement in the coverage of global genetic diversity, studies continue to show that imputation accuracy may be improved by using WGS or high-density SNP data from individuals with similar genetic background to the target population (Thornton and Bermejo 2014;Ahmad et al 2017;Mitt et al 2017). However, for studies performed in non-European populations, WGS or high-density array data are still rare.…”