Evidence map›Paper›PMID 28207879›Full record

ArticlePloS one2017

Comparison of HLA allelic imputation programs.

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 and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
3.9field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 67 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Article
  6. Assessing HLA imputation accuracy in a West African population.bioRxiv : the preprint server for biology · 2023
    Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. A comparison of genotyping arrays.European journal of human genetics : EJHG · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. MiDAS-Meaningful Immunogenetic Data at Scale.PLoS computational biology · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Jason H KarnesDepartment of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, United States of America.ORCID http://orcid.org/0000-0001-5001-3334
Christian M ShafferDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Lisa BastaracheDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
Silvana GaudieriDivision of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Andrew M GlazerDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Heidi E SteinerDepartment of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, United States of America.
Jonathan D MosleyDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Simon MallalDivision of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Joshua C DennyDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Elizabeth J PhillipsDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Dan M RodenDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Murdoch University · AUVanderbilt University · USVanderbilt University Medical Center · USUniversity of Arizona · US

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Pharmacogenomics of Arrhythmia TherapyU19HL065962 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RODEN, DAN M · 2010 to 2014
$17.4M
Understanding and preventing HLA-associated drug reactionsP50GM115305 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI DENNY, JOSHUA C. · 2015 to 2019
$13.0M
CLINICAL PHARMACOLOGY TRAINING PROGRAMT32GM007569 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Bjorn C Knollmann · 1985 to 2026
$12.4M
Genetic predictors of response to anti-TNF therapy in rheumatoid arthritisU01GM092691 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI BRENNER, MICHAEL B., RAYCHAUDHURI, SOUMYA · 2010 to 2014
$7.5M
Vanderbilt Genome-Electronic Records ProjectU01HG004603 · NHGRI · VANDERBILT UNIVERSITY · PI RODEN, DAN M · 2007 to 2011
$7.3M
VESPA: Vanderbilt Electronic Systems for Pharmacogenomic AssessmentRC2GM092618 · NIGMS · VANDERBILT UNIVERSITY · PI DENNY, JOSHUA C., RODEN, DAN M · 2009 to 2010
$6.4M
From GWAS to PheWAS: Scanning the EMR Phenome for Gene-disease AssociationsR01LM010685 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BASTARACHE, LISA · 2011 to 2022
$6.3M
Fine-mapping the MHC associations in rheumatoid arthritis from GWAS dataR01AR062886 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI RAYCHAUDHURI, SOUMYA · 2012 to 2013
$783k
American Heart Association-American Stroke Association 16FTF30130005NCATS NIH HHS UL1 TR000445NHGRI NIH HHS U01 HG004603NHLBI NIH HHS U19 HL065962NIAMS NIH HHS R01 AR062886NIGMS NIH HHS P50 GM115305NIGMS NIH HHS RC2 GM092618NIGMS NIH HHS T32 GM007569NIGMS NIH HHS U01 GM092691NLM NIH HHS R01 LM010685
6 · The paper itself

Abstract

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.

Indexed as

AllelesBlack or African AmericanFemaleGene FrequencyGenome-Wide Association StudyGenotypeHaplotypesHLA AntigensHumansMaleMiddle AgedPolymorphism, Single NucleotideWhite PeopleHLA Antigens

Identifiers

PMID28207879
PMCPMC5312875
OpenAlexW2588121500

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.