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

Authors :
Christley S
Aguiar A
Blanck G
Breden F
Bukhari SAC
Busse CE
Jaglale J
Harikrishnan SL
Laserson U
Peters B
Rocha A
Schramm CA
Taylor S
Vander Heiden JA
Zimonja B
Watson CT
Corrie B
Cowell LG
Source :
Frontiers in big data [Front Big Data] 2020 Jun 17; Vol. 3, pp. 22. Date of Electronic Publication: 2020 Jun 17 (Print Publication: 2020).
Publication Year :
2020

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.<br /> (Copyright © 2020 Christley, Aguiar, Blanck, Breden, Bukhari, Busse, Jaglale, Harikrishnan, Laserson, Peters, Rocha, Schramm, Taylor, Vander Heiden, Zimonja, Watson, Corrie and Cowell.)

Details

Language :
English
ISSN :
2624-909X
Volume :
3
Database :
MEDLINE
Journal :
Frontiers in big data
Publication Type :
Academic Journal
Accession number :
33693395
Full Text :
https://doi.org/10.3389/fdata.2020.00022