Evidence map›Paper›PMID 26430804›Full record

ArticleAmerican journal of human genetics2015

Imputation of KIR Types from SNP Variation Data.

Damjan Vukcevic, James A Traherne, Sigrid Næss, Eva Ellinghaus, Yoichiro Kamatani, Alexander Dilthey, Mark Lathrop, Tom H Karlsen, Andre Franke, Miriam Moffatt and 5 more

Open access · hybridAbstract readComparative Study
In one paragraph

Article in American journal of human genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

46 citing papers in PubMed, 81 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long-Read Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  8. Review
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  18. Review
  19. Review
  20. HIV-1 and human genetic variation.Nature reviews. Genetics · 2021
    Review
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

15 authors at 7 institutions in 7 countries.

Damjan VukcevicStatistical Genetics, Murdoch Childrens Research Institute, Parkville, VIC 3052, Australia; School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia.
James A TraherneCambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK; Division of Immunology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK.
Sigrid NæssResearch Institute of Internal Medicine, Department of Cancer Medicine, Surgery, and Transplantation, Oslo University Hospital Rikshospitalet, Postboks 4950, Nydalen, 0424 Oslo, Norway; Norwegian PSC Research Center, Division of Cancer, Surgery, and Transplantation, Oslo University Hospital, Postboks 4950, Nydalen, 0424 Oslo, Norway.
Eva EllinghausInstitute of Clinical Molecular Biology, Christian-Albrechts University of Kiel, Schittenhelmstraße 12, 24105 Kiel, Germany.
Yoichiro KamataniFondation Jean Dausset, Centre d'Etude du Polymorphisme Humain, 27 Rue Juliette Dodu, 75010 Paris, France; RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
Alexander DiltheyWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
Mark LathropMcGill University and Génome Québec Innovation Centre, Montreal, 740 Dr. Penfield Avenue, Room 7104, Montreal, QC H3A 0G1, Canada; Fondation Jean Dausset, Centre d'Etude du Polymorphisme Humain, 27 Rue Juliette Dodu, 75010 Paris, France.
Tom H KarlsenResearch Institute of Internal Medicine, Department of Cancer Medicine, Surgery, and Transplantation, Oslo University Hospital Rikshospitalet, Postboks 4950, Nydalen, 0424 Oslo, Norway; K.G. Jebsen Inflammation Research Centre, Institute of Clinical Medicine, University of Oslo, Postboks 1171, Blindern, 0318 Oslo, Norway.
Andre FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts University of Kiel, Schittenhelmstraße 12, 24105 Kiel, Germany.
Miriam MoffattNational Heart and Lung Institute, Imperial College London, Royal Brompton Campus, Dovehouse Street, London SW3 6LY, UK.
William CooksonNational Heart and Lung Institute, Imperial College London, Royal Brompton Campus, Dovehouse Street, London SW3 6LY, UK.
John TrowsdaleCambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK; Division of Immunology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK.
Gil McVeanWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
Stephen SawcerDepartment of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK.
Stephen LeslieStatistical Genetics, Murdoch Childrens Research Institute, Parkville, VIC 3052, Australia; School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia. Electronic address: stephen.leslie@mcri.edu.au.
University of Cambridge · GBCentre for Human Genetics · GBChristian-Albrechts-Universität zu Kiel · DEFondation Jean Dausset-CEPH · FRImperial College London · GBOslo University Hospital · NOThe University of Melbourne · AU

Funding

Medical Research Council G0901682Wellcome Trust 097117Wellcome Trust 100140Wellcome Trust 100956
6 · The paper itself

Abstract

Large population studies of immune system genes are essential for characterizing their role in diseases, including autoimmune conditions. Of key interest are a group of genes encoding the killer cell immunoglobulin-like receptors (KIRs), which have known and hypothesized roles in autoimmune diseases, resistance to viruses, reproductive conditions, and cancer. These genes are highly polymorphic, which makes typing expensive and time consuming. Consequently, despite their importance, KIRs have been little studied in large cohorts. Statistical imputation methods developed for other complex loci (e.g., human leukocyte antigen [HLA]) on the basis of SNP data provide an inexpensive high-throughput alternative to direct laboratory typing of these loci and have enabled important findings and insights for many diseases. We present KIR∗IMP, a method for imputation of KIR copy number. We show that KIR∗IMP is highly accurate and thus allows the study of KIRs in large cohorts and enables detailed investigation of the role of KIRs in human disease.

Indexed as

Genetic Predisposition to DiseaseAsthmaCase-Control StudiesCohort StudiesDermatitis, AtopicDNA Copy Number VariationsEuropeFamilyFemaleGenotypeHigh-Throughput Nucleotide SequencingHumansMalePolymorphism, Single NucleotideReceptors, KIRSequence Analysis, DNAReceptors, KIR

Identifiers

PMID26430804
PMCPMC4596914
OpenAlexW2166894188

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.