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Front Immunol. 2017 Nov 1;8:1418. doi: 10.3389/fimmu.2017.01418. eCollection 2017.

Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data.

Author information

1
Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada.
2
Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
3
La Jolla Institute for Allergy and Immunology, La Jolla, CA, United States.
4
Department of Microbiology and Immunology, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, United States.
5
Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.
6
Division of B Cell Immunology, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany.
7
Department of Neurology, Yale University School of Medicine, New Haven, CT, United States.
8
Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States.
9
Department of Pathology, Yale University School of Medicine, New Haven, CT, United States.
10
entre of Genomics and Policy, McGill University, Montreal, QC, Canada.
11
Public Health Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
12
Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel.
13
Department of Genetics and Genome Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
14
Immunology-Immunopathology-Immunotherapy (i3 & i2B), Sorbonne Université, Paris, France.
15
IMGT, LIGM, Institut de Génétique Humaine IGH, CNRS, University of Montpellier, Montpellier, France.
16
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, NSW, Australia.
17
Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada.
18
Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, United States.
19
Faculty of Health Sciences, Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada.
20
Department of Microbiology, Boston University School of Medicine, Boston, MA, United States.
21
Department of Mathematics and Statistics, Boston University, Boston, MA, United States.

Abstract

High-throughput sequencing (HTS) of immunoglobulin (B-cell receptor, antibody) and T-cell receptor repertoires has increased dramatically since the technique was introduced in 2009 (1-3). This experimental approach explores the maturation of the adaptive immune system and its response to antigens, pathogens, and disease conditions in exquisite detail. It holds significant promise for diagnostic and therapy-guiding applications. New technology often spreads rapidly, sometimes more rapidly than the understanding of how to make the products of that technology reliable, reproducible, or usable by others. As complex technologies have developed, scientific communities have come together to adopt common standards, protocols, and policies for generating and sharing data sets, such as the MIAME protocols developed for microarray experiments. The Adaptive Immune Receptor Repertoire (AIRR) Community formed in 2015 to address similar issues for HTS data of immune repertoires. The purpose of this perspective is to provide an overview of the AIRR Community's founding principles and present the progress that the AIRR Community has made in developing standards of practice and data sharing protocols. Finally, and most important, we invite all interested parties to join this effort to facilitate sharing and use of these powerful data sets (join@airr-community.org).

KEYWORDS:

B-cell receptors; T-cell receptors; antibodies; community standards; data sharing; high-throughput sequencing; immunogenetics; immunoglobulins

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