Comparison of HLA allelic imputation programs.

Imputation of human leukocyte antigen (HLA) alleles from SNP-level data is attractive due to importance of HLA alleles in human disease, widespread availability of genome-wide association study (GWAS) data, and expertise required for HLA sequencing. However, comprehensive evaluations of HLA imputati...

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Main Authors: Jason H Karnes, Christian M Shaffer, Lisa Bastarache, Silvana Gaudieri, Andrew M Glazer, Heidi E Steiner, Jonathan D Mosley, Simon Mallal, Joshua C Denny, Elizabeth J Phillips, Dan M Roden
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0172444&type=printable
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author Jason H Karnes
Christian M Shaffer
Lisa Bastarache
Silvana Gaudieri
Andrew M Glazer
Heidi E Steiner
Jonathan D Mosley
Simon Mallal
Joshua C Denny
Elizabeth J Phillips
Dan M Roden
author_facet Jason H Karnes
Christian M Shaffer
Lisa Bastarache
Silvana Gaudieri
Andrew M Glazer
Heidi E Steiner
Jonathan D Mosley
Simon Mallal
Joshua C Denny
Elizabeth J Phillips
Dan M Roden
author_sort Jason H Karnes
collection DOAJ
description Imputation of human leukocyte antigen (HLA) alleles from SNP-level data is attractive due to importance of HLA alleles in human disease, widespread availability of genome-wide association study (GWAS) data, and expertise required for HLA sequencing. However, comprehensive evaluations of HLA imputations programs are limited. We compared HLA imputation results of HIBAG, SNP2HLA, and HLA*IMP:02 to sequenced HLA alleles in 3,265 samples from BioVU, a de-identified electronic health record database coupled to a DNA biorepository. We performed four-digit HLA sequencing for HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1 using long-read 454 FLX sequencing. All samples were genotyped using both the Illumina HumanExome BeadChip platform and a GWAS platform. Call rates and concordance rates were compared by platform, frequency of allele, and race/ethnicity. Overall concordance rates were similar between programs in European Americans (EA) (0.975 [SNP2HLA]; 0.939 [HLA*IMP:02]; 0.976 [HIBAG]). SNP2HLA provided a significant advantage in terms of call rate and the number of alleles imputed. Concordance rates were lower overall for African Americans (AAs). These observations were consistent when accuracy was compared across HLA loci. All imputation programs performed similarly for low frequency HLA alleles. Higher concordance rates were observed when HLA alleles were imputed from GWAS platforms versus the HumanExome BeadChip, suggesting that high genomic coverage is preferred as input for HLA allelic imputation. These findings provide guidance on the best use of HLA imputation methods and elucidate their limitations.
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spelling doaj-art-49d5bdb819ea46ffb68fc2dbe3c44b812025-08-20T02:31:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01122e017244410.1371/journal.pone.0172444Comparison of HLA allelic imputation programs.Jason H KarnesChristian M ShafferLisa BastaracheSilvana GaudieriAndrew M GlazerHeidi E SteinerJonathan D MosleySimon MallalJoshua C DennyElizabeth J PhillipsDan M RodenImputation of human leukocyte antigen (HLA) alleles from SNP-level data is attractive due to importance of HLA alleles in human disease, widespread availability of genome-wide association study (GWAS) data, and expertise required for HLA sequencing. However, comprehensive evaluations of HLA imputations programs are limited. We compared HLA imputation results of HIBAG, SNP2HLA, and HLA*IMP:02 to sequenced HLA alleles in 3,265 samples from BioVU, a de-identified electronic health record database coupled to a DNA biorepository. We performed four-digit HLA sequencing for HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1 using long-read 454 FLX sequencing. All samples were genotyped using both the Illumina HumanExome BeadChip platform and a GWAS platform. Call rates and concordance rates were compared by platform, frequency of allele, and race/ethnicity. Overall concordance rates were similar between programs in European Americans (EA) (0.975 [SNP2HLA]; 0.939 [HLA*IMP:02]; 0.976 [HIBAG]). SNP2HLA provided a significant advantage in terms of call rate and the number of alleles imputed. Concordance rates were lower overall for African Americans (AAs). These observations were consistent when accuracy was compared across HLA loci. All imputation programs performed similarly for low frequency HLA alleles. Higher concordance rates were observed when HLA alleles were imputed from GWAS platforms versus the HumanExome BeadChip, suggesting that high genomic coverage is preferred as input for HLA allelic imputation. These findings provide guidance on the best use of HLA imputation methods and elucidate their limitations.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0172444&type=printable
spellingShingle Jason H Karnes
Christian M Shaffer
Lisa Bastarache
Silvana Gaudieri
Andrew M Glazer
Heidi E Steiner
Jonathan D Mosley
Simon Mallal
Joshua C Denny
Elizabeth J Phillips
Dan M Roden
Comparison of HLA allelic imputation programs.
PLoS ONE
title Comparison of HLA allelic imputation programs.
title_full Comparison of HLA allelic imputation programs.
title_fullStr Comparison of HLA allelic imputation programs.
title_full_unstemmed Comparison of HLA allelic imputation programs.
title_short Comparison of HLA allelic imputation programs.
title_sort comparison of hla allelic imputation programs
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0172444&type=printable
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