Evidence map›Paper›PMID 34479742›Full record

ArticleHuman immunology2021

Challenges for the standardized reporting of NGS HLA genotyping: Surveying gaps between clinical and research laboratories.

Kazutoyo Osoegawa, Gonzalo Montero-Martín, Kalyan C Mallempati, Miranda Bauer, Robert P Milius, Martin Maiers, Marcelo A Fernández-Viña, Steven J Mack

Open access · greenAbstract read
In one paragraph

Article in Human immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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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

8 authors at 3 institutions in 1 country.

Kazutoyo OsoegawaHistocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA 94303, USA. Electronic address: kazutoyo@stanford.edu.
Gonzalo Montero-MartínHistocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA 94303, USA.
Kalyan C MallempatiHistocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA 94303, USA.
Miranda BauerVendor and Laboratory Services, National Marrow Donor Program, Minneapolis, MN, USA.
Robert P MiliusBioinformatics Research, National Marrow Donor Program, Minneapolis, MN, USA.
Martin MaiersBioinformatics Research, National Marrow Donor Program, Minneapolis, MN, USA; Center for International Blood and Marrow Transplant Research, Minneapolis, MN 55401, USA.
Marcelo A Fernández-ViñaHistocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA 94303, USA; Department of Pathology, Stanford University School of Medicine, Palo Alto, CA 94304, USA.
Steven J MackDepartment of Pediatrics, University of California, San Francisco, Oakland, CA 94501, USA.
Stanford Blood Center · USNational Marrow Donor Program · USUniversity of California, San Francisco · US

Funding

Integrated Exchange and Storage of Current- and Future-Generation Immunogenomic DataR01AI128775 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JILL Allison HOLLENBACH, STEVEN JOHN MACK · 2017 to 2026
$4.5M
NIAID NIH HHS R01 AI128775
6 · The paper itself

Abstract

Next generation sequencing (NGS) is being applied for HLA typing in research and clinical settings. NGS HLA typing has made it feasible to sequence exons, introns and untranslated regions simultaneously, with significantly reduced labor and reagent cost per sample, rapid turnaround time, and improved HLA genotype accuracy. NGS technologies bring challenges for cost-effective computation, data processing and exchange of NGS-based HLA data. To address these challenges, guidelines and specifications such as Genotype List (GL) String, Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING), and Histoimmunogenetics Markup Language (HML) were proposed to streamline and standardize reporting of HLA genotypes. As part of the 17th International HLA and Immunogenetics Workshop (IHIW), we implemented standards and systems for HLA genotype reporting that included GL String, MIRING and HML, and found that misunderstanding or misinterpretations of these standards led to inconsistencies in the reporting of NGS HLA genotyping results. This may be due in part to a historical lack of centralized data reporting standards in the histocompatibility and immunogenetics community. We have worked with software and database developers, clinicians and scientists to address these issues in a collaborative fashion as part of the Data Standard Hackathons (DaSH) for NGS. Here we report several categories of challenges to the consistent exchange of NGS HLA genotyping data we have observed. We hope to address these challenges in future DaSH for NGS efforts.

Indexed as

Genotyping TechniquesHigh-Throughput Nucleotide SequencingHistocompatibility TestingHLA AntigensHumansImmunogeneticsLaboratoriesSequence Analysis, DNASoftwareHLA AntigensAllelic ambiguityGenotypic ambiguityGL StringHMLMIRING

Identifiers

PMID34479742
PMCPMC8545853
OpenAlexW3197062952

What OpenQuestion holds

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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.