A standardized file format for representing V(D)J analysis results. VDJML facilitates downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library called VDJMLpy. It's a module for working with the results of immune receptor sequence alignment in VDJML format.

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VDJMLpy classification

VDJMLpy specifications

Software type:
Package
Restrictions to use:
None
Output format:
VDJML
Programming languages:
C++, Python
Computer skills:
Advanced
Stability:
Stable
Interface:
Command line interface
Input format:
FASTA, FASTQ, QUAL
Operating system:
Unix/Linux, Mac OS
License:
Boost Software License
Version:
0.1.4

Credits

Publications

  • (Toby et al., 2016) VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements. BMC Bioinformatics.
    PMID: 27766961

Institution(s)

Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, USA; Bank of America Corporate Center, Charlotte, NC, USA; Broad Institute, Cambridge, MA, USA; Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA; Department of Biological Sciences and The IRMACS Centre, Simon Fraser University, Burnaby, BC, Canada; Department of Immunobiology, University of Arizona School of Medicine, Tucson, AZ, USA; New Zealand eScience Infrastructure, University of Auckland, Auckland, New Zealand; Texas Advanced Computing Center, Research Office Complex 1.101, J.J. Pickle Research Campus, Austin, TX, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; School of Biomedical Engineering, Science and Health Systems and Department of Microbiology and Immunology, College of Medicine, Drexel University, Philadelphia, PA, USA; The IRMACS Centre, Simon Fraser University, Burnaby, BC, Canada; School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA; Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX, USA; Stanford University School of Medicine, Stanford, CA, USA; Department of Molecular Biology and Biochemistry and Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada; Department of Pathology, Yale School of Medicine, New Haven, CT, USA; J. Craig Venter Institute, La Jolla, CA, USA; Department of Pathology, University of California, San Diego, La Jolla, CA, USA; Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA

Funding source(s)

This tool was supported by a Burroughs Welcome Fund Career Award and an NIAID-funded R01 (AI097403), by the Bioinformatics Support Contract (HHSN272201200028C) and the National Institute of Allergy and Infectious Diseases (grant U19 AI090019), by National Institute of Allergy and Infectious Diseases (grant R01 AI104739), by a PhRMA foundation pre-doctoral informatics fellowship and by the National Library of Medicine of the National Institutes of Health (T15 LM07056).

Link to literature

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