tutorial arrow
×
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

VDJMLpy

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.

User report

tutorial arrow
×
Vote up tools and offer feedback
Give value to tools and make your expertise visible

0 user reviews

0 user reviews

No review has been posted.

VDJMLpy forum

tutorial arrow
×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.

No open topic.

VDJMLpy versioning

tutorial arrow
×
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.

No versioning.

VDJMLpy classification

VDJMLpy specifications

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

VDJMLpy support

Maintainer

  • Lindsay G. Cowell <>

Credits

tutorial arrow
×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.

Publications

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

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.