Literature DB >> 33693395

The ADC API: A Web API for the Programmatic Query of the AIRR Data Commons.

Scott Christley1, Ademar Aguiar2,3, George Blanck4, Felix Breden5, Syed Ahmad Chan Bukhari6, Christian E Busse7, Jerome Jaglale5, Srilakshmy L Harikrishnan7, Uri Laserson8, Bjoern Peters9,10, Artur Rocha2, Chaim A Schramm11, Sarah Taylor12, Jason Anthony Vander Heiden13, Bojan Zimonja5, Corey T Watson14, Brian Corrie5, Lindsay G Cowell1.   

Abstract

The Adaptive Immune Receptor Repertoire (AIRR) Community is a research-driven group that is establishing a clear set of community-accepted data and metadata standards; standards-based reference implementation tools; and policies and practices for infrastructure to support the deposit, curation, storage, and use of high-throughput sequencing data from B-cell and T-cell receptor repertoires (AIRR-seq data). The AIRR Data Commons is a distributed system of data repositories that utilizes a common data model, a common query language, and common interoperability formats for storage, query, and downloading of AIRR-seq data. Here is described the principal technical standards for the AIRR Data Commons consisting of the AIRR Data Model for repertoires and rearrangements, the AIRR Data Commons (ADC) API for programmatic query of data repositories, a reference implementation for ADC API services, and tools for querying and validating data repositories that support the ADC API. AIRR-seq data repositories can become part of the AIRR Data Commons by implementing the data model and API. The AIRR Data Commons allows AIRR-seq data to be reused for novel analyses and empowers researchers to discover new biological insights about the adaptive immune system.
Copyright © 2020 Christley, Aguiar, Blanck, Breden, Bukhari, Busse, Jaglale, Harikrishnan, Laserson, Peters, Rocha, Schramm, Taylor, Vander Heiden, Zimonja, Watson, Corrie and Cowell.

Entities:  

Keywords:  Rep-Seq; antibody; community standards; data sharing; immunoglobulin; immunology; repertoire analysis

Year:  2020        PMID: 33693395      PMCID: PMC7931935          DOI: 10.3389/fdata.2020.00022

Source DB:  PubMed          Journal:  Front Big Data        ISSN: 2624-909X


  9 in total

1.  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

2.  Diversity in immunogenomics: the value and the challenge.

Authors:  Houda Alachkar; Cathrine Scheepers; Corey T Watson; Gunilla B Karlsson Hedestam; Serghei Mangul; Kerui Peng; Yana Safonova; Mikhail Shugay; Alice B Popejoy; Oscar L Rodriguez; Felix Breden; Petter Brodin; Amanda M Burkhardt; Carlos Bustamante; Van-Mai Cao-Lormeau; Martin M Corcoran; Darragh Duffy; Macarena Fuentes-Guajardo; Ricardo Fujita; Victor Greiff; Vanessa D Jönsson; Xiao Liu; Lluis Quintana-Murci; Maura Rossetti; Jianming Xie; Gur Yaari; Wei Zhang; Malak S Abedalthagafi; Khalid O Adekoya; Rahaman A Ahmed; Wei-Chiao Chang; Clive Gray; Yusuke Nakamura; William D Lees; Purvesh Khatri
Journal:  Nat Methods       Date:  2021-06       Impact factor: 47.990

3.  The Future of Blood Testing Is the Immunome.

Authors:  Ramy A Arnaout; Eline T Luning Prak; Nicholas Schwab; Florian Rubelt
Journal:  Front Immunol       Date:  2021-03-15       Impact factor: 7.561

4.  T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates.

Authors:  Scott Christley; Jared Ostmeyer; Lisa Quirk; Wei Zhang; Bradley Sirak; Anna R Giuliano; Song Zhang; Nancy Monson; Jasmin Tiro; Elena Lucas; Lindsay G Cowell
Journal:  Front Immunol       Date:  2021-04-02       Impact factor: 7.561

5.  Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences.

Authors:  Tobias H Olsen; Fergus Boyles; Charlotte M Deane
Journal:  Protein Sci       Date:  2021-10-29       Impact factor: 6.725

Review 6.  Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery.

Authors:  Wiktoria Wilman; Sonia Wróbel; Weronika Bielska; Piotr Deszynski; Paweł Dudzic; Igor Jaszczyszyn; Jędrzej Kaniewski; Jakub Młokosiewicz; Anahita Rouyan; Tadeusz Satława; Sandeep Kumar; Victor Greiff; Konrad Krawczyk
Journal:  Brief Bioinform       Date:  2022-07-18       Impact factor: 13.994

7.  Global patterns of antigen receptor repertoire disruption across adaptive immune compartments in COVID-19.

Authors:  Magdalene Joseph; Yin Wu; Richard Dannebaum; Florian Rubelt; Iva Zlatareva; Anna Lorenc; Zhipei Gracie Du; Daniel Davies; Fernanda Kyle-Cezar; Abhishek Das; Sarah Gee; Jeffrey Seow; Carl Graham; Dilduz Telman; Clara Bermejo; Hai Lin; Hosseinali Asgharian; Adam G Laing; Irene Del Molino Del Barrio; Leticia Monin; Miguel Muñoz-Ruiz; Duncan R McKenzie; Thomas S Hayday; Isaac Francos-Quijorna; Shraddha Kamdar; Richard Davis; Vasiliki Sofra; Florencia Cano; Efstathios Theodoridis; Lauren Martinez; Blair Merrick; Karen Bisnauthsing; Kate Brooks; Jonathan Edgeworth; John Cason; Christine Mant; Katie J Doores; Pierre Vantourout; Khai Luong; Jan Berka; Adrian C Hayday
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-09       Impact factor: 12.779

Review 8.  High-throughput and single-cell T cell receptor sequencing technologies.

Authors:  Joy A Pai; Ansuman T Satpathy
Journal:  Nat Methods       Date:  2021-07-19       Impact factor: 47.990

9.  AbDiver-A tool to explore the natural antibody landscape to aid therapeutic design.

Authors:  Jakub Młokosiewicz; Piotr Deszyński; Wiktoria Wilman; Igor Jaszczyszyn; Rajkumar Ganesan; Aleksandr Kovaltsuk; Jinwoo Leem; Jacob Galson; Konrad Krawczyk
Journal:  Bioinformatics       Date:  2022-03-11       Impact factor: 6.931

  9 in total

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