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Rare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools.

TitleRare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools.
Publication TypeJournal Article
Year of Publication2019
AuthorsSariya S, Lee JH, Mayeux R, Vardarajan BN, Reyes-Dumeyer D, Manly JJ, Brickman AM, Lantigua R, Medrano M, Jimenez-Velazquez IZ, Tosto G
JournalFront Genet
Volume10
Pagination239
Date Published2019
ISSN1664-8021
Abstract

Background: Imputation has become a standard approach in genome-wide association studies (GWAS) to infer untyped markers. Although feasibility for common variants imputation is well established, we aimed to assess rare and ultra-rare variants' imputation in an admixed Caribbean Hispanic population (CH).
Methods: We evaluated imputation accuracy in CH ( = 1,000), focusing on rare (0.1% ≤ minor allele frequency (MAF) ≤ 1%) and ultra-rare (MAF < 0.1%) variants. We used two reference panels, the Haplotype Reference Consortium (HRC; = 27,165) and 1000 Genome Project (1000G phase 3; = 2,504) and multiple phasing (SHAPEIT, Eagle2) and imputation algorithms (IMPUTE2, MACH-Admix). To assess imputation quality, we reported: (a) high-quality variant counts according to imputation tools' internal indexes (e.g., IMPUTE2 "Info" ≥ 80%). (b) Wilcoxon Signed-Rank Test comparing imputation quality for genotyped variants that were masked and imputed; (c) Cohen's kappa coefficient to test agreement between imputed and whole-exome sequencing (WES) variants; (d) imputation of G206A mutation in the (ultra-rare in the general population an more frequent in CH) followed by confirmation genotyping. We also tested ancestry proportion (European, African and Native American) against WES-imputation mismatches in a Poisson regression fashion.
Results: SHAPEIT2 retrieved higher percentage of imputed high-quality variants than Eagle2 (rare: 51.02% vs. 48.60%; ultra-rare 0.66% vs. 0.65%, Wilcoxon -value < 0.001). SHAPEIT-IMPUTE2 employing HRC outperformed 1000G (64.50% vs. 59.17%; 1.69% vs. 0.75% for high-quality rare and ultra-rare variants, respectively, Wilcoxon -value < 0.001). SHAPEIT-IMPUTE2 outperformed MaCH-Admix. Compared to 1000G, HRC-imputation retrieved a higher number of high-quality rare and ultra-rare variants, despite showing lower agreement between imputed and WES variants (e.g., rare: 98.86% for HRC vs. 99.02% for 1000G). High Kappa ( = 0.99) was observed for both reference panels. Twelve G206A mutation carriers were imputed and all validated by confirmation genotyping. African ancestry was associated with higher imputation errors for uncommon and rare variants (-value < 1e-05).
Conclusion: Reference panels with larger numbers of haplotypes can improve imputation quality for rare and ultra-rare variants in admixed populations such as CH. Ethnic composition is an important predictor of imputation accuracy, with higher African ancestry associated with poorer imputation accuracy.

DOI10.3389/fgene.2019.00239
Pubmed Linkhttps://www.ncbi.nlm.nih.gov/pubmed/31001313?dopt=Abstract
page_expoExternal
Alternate JournalFront Genet
PubMed ID31001313
PubMed Central IDPMC6456789
Grant ListR01 AG058918 / AG / NIA NIH HHS / United States
R37 AG015473 / AG / NIA NIH HHS / United States
RF1 AG054023 / AG / NIA NIH HHS / United States
RF1 AG015473 / AG / NIA NIH HHS / United States
R56 AG051876 / AG / NIA NIH HHS / United States
R21 AG054832 / AG / NIA NIH HHS / United States

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