Evidence map›Paper›PMID 33693395›Full record

ArticleFrontiers in big data2020

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

Scott Christley, Ademar Aguiar, George Blanck, Felix Breden, Syed Ahmad Chan Bukhari, Christian E Busse, Jerome Jaglale, Srilakshmy L Harikrishnan, Uri Laserson, Bjoern Peters and 8 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in big data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 43 citations in OpenAlex.

  1. Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Machine learning in AIRR diagnostics: Advances and applications.Immunoinformatics (Amsterdam, Netherlands) · 2025
    Article
  5. Article
  6. Challenges and future directions of AIRR-seq-based diagnostics.Immunoinformatics (Amsterdam, Netherlands) · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
  17. Article
  18. NAIR: Network Analysis of Immune Repertoire.Frontiers in immunology · 2023
    Article
  19. Global patterns of antigen receptor repertoire disruption across adaptive immune compartments in COVID-19.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 13 institutions in 4 countries.

Scott ChristleyDepartment of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, United States.
Ademar AguiarCentre for Information Systems and Computer Graphics, Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.
George BlanckDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, United States.
Felix BredenDepartment of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada.
Syed Ahmad Chan BukhariDivision of Computer Science, Mathematics and Science (Healthcare Informatics), College of Professional Studies, St. John's University, New York, NY, United States.
Christian E BusseDivision of B Cell Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Jerome JaglaleDepartment of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada.
Srilakshmy L HarikrishnanDivision of B Cell Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Uri LasersonDepartment of Genetics and Genome Sciences, Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Bjoern PetersDivision of Vaccine Discover, La Jolla Institute for Immunology, La Jolla, CA, United States.
Artur RochaCentre for Information Systems and Computer Graphics, Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.
Chaim A SchrammVaccine Research Center, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, United States.
Sarah Taylor10x Genomics, Pleasanton, CA, United States.
Jason Anthony Vander HeidenDepartment of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA, United States.
Bojan ZimonjaDepartment of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada.
Corey T WatsonDepartment of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, United States.
Brian CorrieDepartment of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada.
Lindsay G CowellDepartment of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, United States.
Simon Fraser University · CAGerman Cancer Research Center · DE10X Genomics (United States) · USIcahn School of Medicine at Mount Sinai · USINESC TEC · PTNational Institute of Allergy and Infectious Diseases · USSouthwestern Medical CenterSt. John's University · USThe University of Texas Southwestern Medical Center · USUniversidade do Porto · PTUniversity of California, San Diego · USUniversity of Louisville · USUniversity of South Florida · US

Funding

RepServer: Antigen Receptor Repertoire Analysis Pipelines via the WWWR01AI097403 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI COWELL, LINDSAY G. · 2012 to 2016
$3.2M
NIAID NIH HHS R01 AI097403
6 · The paper itself

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.

Indexed as

antibodycommunity standardsdata sharingimmunoglobulinimmunologyrepertoire analysisRep-Seq

Identifiers

PMID33693395
PMCPMC7931935
OpenAlexW3029868869

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.