Literature DB >> 29944754

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories.

Brian D Corrie1, Nishanth Marthandan1,2, Bojan Zimonja1, Jerome Jaglale1, Yang Zhou1, Emily Barr1, Nicole Knoetze1, Frances M W Breden1, Scott Christley3, Jamie K Scott2,4, Lindsay G Cowell3, Felix Breden1,5.   

Abstract

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  cancer immunotherapy; data sharing; distributed data federation; immune repertoires; therapeutic antibodies; vaccines

Mesh:

Substances:

Year:  2018        PMID: 29944754      PMCID: PMC6344122          DOI: 10.1111/imr.12666

Source DB:  PubMed          Journal:  Immunol Rev        ISSN: 0105-2896            Impact factor:   12.988


  38 in total

1.  HLA class I-associated expansion of TRBV11-2 T cells in multisystem inflammatory syndrome in children.

Authors:  Rebecca A Porritt; Lisa Paschold; Magali Noval Rivas; Mary Hongying Cheng; Lael M Yonker; Harsha Chandnani; Merrick Lopez; Donjete Simnica; Christoph Schultheiß; Chintda Santiskulvong; Jennifer Van Eyk; John K McCormick; Alessio Fasano; Ivet Bahar; Mascha Binder; Moshe Arditi
Journal:  J Clin Invest       Date:  2021-05-17       Impact factor: 14.808

2.  Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases.

Authors:  Pierre Barennes; Valentin Quiniou; Mikhail Shugay; Evgeniy S Egorov; Alexey N Davydov; Dmitriy M Chudakov; Imran Uddin; Mazlina Ismail; Theres Oakes; Benny Chain; Anne Eugster; Karl Kashofer; Peter P Rainer; Samuel Darko; Amy Ransier; Daniel C Douek; David Klatzmann; Encarnita Mariotti-Ferrandiz
Journal:  Nat Biotechnol       Date:  2020-09-07       Impact factor: 54.908

Review 3.  How repertoire data are changing antibody science.

Authors:  Claire Marks; Charlotte M Deane
Journal:  J Biol Chem       Date:  2020-05-14       Impact factor: 5.157

4.  Data Sharing and Reuse: A Method by the AIRR Community.

Authors:  Brian D Corrie; Scott Christley; Christian E Busse; Lindsay G Cowell; Kira C M Neller; Florian Rubelt; Nicholas Schwab
Journal:  Methods Mol Biol       Date:  2022

Review 5.  Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies.

Authors:  Rahmad Akbar; Habib Bashour; Puneet Rawat; Philippe A Robert; Eva Smorodina; Tudor-Stefan Cotet; Karine Flem-Karlsen; Robert Frank; Brij Bhushan Mehta; Mai Ha Vu; Talip Zengin; Jose Gutierrez-Marcos; Fridtjof Lund-Johansen; Jan Terje Andersen; Victor Greiff
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

6.  Immune receptor CDR3 chemical features that preserve sequence information are highly efficient in reflecting survival distinctions: A pan-cancer analysis.

Authors:  Brooke E Mcbreairty; Boris I Chobrutskiy; Andrea Chobrutskiy; Etienne C Gozlan; Michael J Diaz; George Blanck
Journal:  Biomed Rep       Date:  2022-06-09

7.  TCRdb: a comprehensive database for T-cell receptor sequences with powerful search function.

Authors:  Si-Yi Chen; Tao Yue; Qian Lei; An-Yuan Guo
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

8.  How to design preclinical studies in nanomedicine and cell therapy to maximize the prospects of clinical translation.

Authors:  John P A Ioannidis; Betty Y S Kim; Alan Trounson
Journal:  Nat Biomed Eng       Date:  2018-11-08       Impact factor: 25.671

9.  ClonoMatch: a tool for identifying homologous immunoglobulin and T cell receptor sequences in large databases.

Authors:  Taylor Jones; Samuel B Day; Luke Myers; James E Crowe; Cinque Soto
Journal:  Bioinformatics       Date:  2020-12-16       Impact factor: 6.937

Review 10.  Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics.

Authors:  Rahul Khetan; Robin Curtis; Charlotte M Deane; Johannes Thorling Hadsund; Uddipan Kar; Konrad Krawczyk; Daisuke Kuroda; Sarah A Robinson; Pietro Sormanni; Kouhei Tsumoto; Jim Warwicker; Andrew C R Martin
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

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