Evidence map›Paper›PMID 27766961›Full record

ArticleBMC bioinformatics2016

VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements.

Inimary T Toby, Mikhail K Levin, Edward A Salinas, Scott Christley, Sanchita Bhattacharya, Felix Breden, Adam Buntzman, Brian Corrie, John Fonner, Namita T Gupta and 13 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

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  7. T Cell Receptor Profiling in Type 1 Diabetes.Current diabetes reports · 2017
    Review
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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

23 authors at 13 institutions in 3 countries.

Inimary T TobyDepartment of Clinical Sciences, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-9066, USA.
Mikhail K LevinBank of America Corporate Center, 100 North Tryon Street, Charlotte, NC, 28202, USA.
Edward A SalinasBroad Institute, 75 Ames Street, Cambridge, MA, 02142, USA.
Scott ChristleyDepartment of Clinical Sciences, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-9066, USA.
Sanchita BhattacharyaInstitute for Computational Health Sciences, University of California San Francisco, Mission Hall, 550 16th Street, 4th Floor, Box 0110, San Francisco, CA, 94158, USA.
Felix BredenDepartment of Biological Sciences and The IRMACS Centre, Simon Fraser University, 8888 University Drive, Burnaby, V5A 1S6, British Columbia, Canada.
Adam BuntzmanDepartment of Immunobiology, University of Arizona School of Medicine, 1656 E. Mabel Street, P.O. Box 245221, Tucson, AZ, 85724-5221, USA.
Brian CorrieNew Zealand eScience Infrastructure, University of Auckland, Level 10, 49 Symonds Street, Auckland, New Zealand.
John FonnerTexas Advanced Computing Center, Research Office Complex 1.101, J.J. Pickle Research Campus, Building 196, 10100 Burnet Road (R8700), Austin, TX, 78758-4497, USA.
Namita T GuptaInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 505, New Haven, CT, 06511, USA.
Uri HershbergSchool of Biomedical Engineering, Science and Health Systems and Department of Microbiology and Immunology, College of Medicine, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA.
Nishanth MarthandanThe IRMACS Centre (ASB 10905), Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.
Aaron RosenfeldSchool of Biomedical Engineering, Science and Health Systems, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA.
William RoundsDepartment of Neurology and Neurotherapeutics, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-9036, USA.
Florian RubeltStanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305-5101, USA.
Walter ScarboroughTexas Advanced Computing Center, Research Office Complex 1.101, J.J. Pickle Research Campus, Building 196, 10100 Burnet Road (R8700), Austin, TX, 78758-4497, USA.
Jamie K ScottDepartment of Molecular Biology and Biochemistry and Faculty of Health Sciences, Simon Fraser University, Blusson Hall, Room 11300, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.
Mohamed UdumanDepartment of Pathology, Yale School of Medicine, 300 George Street, Suite 505, New Haven, CT, 06511, USA.
Jason A Vander HeidenInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 505, New Haven, CT, 06511, USA.
Richard H ScheuermannJ. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA, 92037, USA.
Nancy MonsonDepartment of Neurology and Neurotherapeutics, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-9036, USA.
Steven H KleinsteinInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 505, New Haven, CT, 06511, USA.
Lindsay G CowellDepartment of Clinical Sciences, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-9066, USA. lindsay.cowell@utsouthwestern.edu.
Yale University · USSimon Fraser University · CASouthwestern Medical CenterDrexel University · USTexas Advanced Computing CenterThe University of Texas Southwestern Medical Center · USBank of America · USBroad Institute · USLa Jolla Institute for Immunology · USNew Zealand eScience Infrastructure · NZStanford University · USUniversity of Arizona · USUniversity of California, San Francisco · US

Funding

Transcriptomics and Repertoire ProfilingP01AI106697 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Donna L. Farber · 2013 to 2026
$31.3M
MEDICAL INFORMATICS RESEARCH TRAINING AT YALET15LM007056 · NLM · YALE UNIVERSITY · PI Mark Bender Gerstein, LUCILA OHNO-MACHADO · 1987 to 2026
$22.2M
Vaccination and infection: indicators of immunological health and responsivenessU19AI090019 · NIAID · STANFORD UNIVERSITY · PI DAVIS, MARK MORRIS · 2010 to 2015
$17.3M
COMPUTATIONAL TOOLS FOR THE ANALYSIS OF HIGH-THROUGHPUT IMMUNOGLOBULIN SEQUENCING EXPERIMENTSR01AI104739 · NIAID · YALE UNIVERSITY · PI KLEINSTEIN, STEVEN H. · 2014 to 2022
$3.6M
RepServer: Antigen Receptor Repertoire Analysis Pipelines via the WWWR01AI097403 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI COWELL, LINDSAY G. · 2012 to 2016
$3.2M
NIAID NIH HHS HHSN272201200028CNIAID NIH HHS P01 AI106697NIAID NIH HHS R01 AI097403NIAID NIH HHS R01 AI104739NIAID NIH HHS U19 AI090019NLM NIH HHS T15 LM007056
6 · The paper itself

Abstract

backgroundThe genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D)J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D)J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D)J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D)J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses.

resultsTo help address this problem, we propose a standardized file format for representing V(D)J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D)J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format.

conclusionsThe VDJML suite will allow users to streamline their V(D)J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https://vdjserver.org/vdjml/ . We welcome participation from the community in developing the file format standard, as well as code contributions.

Indexed as

SoftwareV(D)J RecombinationGenomicsHumansInformation DisseminationReceptors, ImmunologicReceptors, ImmunologicAntigen receptor repertoireC++Data sharingData standardsImmune repertoirePythonRepertoire profilingXML

Identifiers

PMID27766961
PMCPMC5073965
OpenAlexW2527996525

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.