Observed antibody space: a diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences
Open accessAbstract
The antibody repertoires of individuals and groups have been used to explore disease states, understand vaccine responses, and drive therapeutic development. The arrival of B-cell receptor repertoire sequencing has enabled researchers to get a snapshot of these antibody repertoires, and as more data are generated, increasingly in-depth studies are possible. However, most publicly available data only exist as raw FASTQ files, making the data hard to access, process, and compare. The Observed Antibody Space (OAS) database was created in 2018 to offer clean, annotated, and translated repertoire data. In this paper, we describe an update to OAS that has been driven by the increasing volume of data and the appearance of paired (VH/VL) sequence data. OAS is now accessible via a new web server, with standardized search parameters and a new sequence-based search option. The new database provides both nucleotides and amino acids for every sequence, with additional sequence annotations to make the data Minimal Information about Adaptive Immune Receptor Repertoire compliant, and comments on potential problems with the sequence. OAS now contains 25 new studies, including severe acute respiratory syndrome coronavirus 2 data and paired sequencing data. The new database is accessible at http://opig.stats.ox.ac.uk/webapps/oas/, and all data are freely available for download.
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Efforts have been made to create standardized, publicly available repositories for antibody sequencing data.
“Efforts have been made to create standardized, publicly available repositories for these sequencing data [8,9].”
From Computational and artificial intelligence-based methods for antibody development (2023) · cites this paper as [8]
The observed antibody space (OAS) collates variable fragment (Fv) sequences and contains nearly 2 billion sequences spanning 68 different studies.
“The observed antibody space (OAS) collates variable fragment (Fv) sequences and contains nearly 2 billion sequences spanning 68 different studies [8].”
From Computational and artificial intelligence-based methods for antibody development (2023) · cites this paper as [8]
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References 34 · Cited by 319
- Authors
- Olsen, T. H., Boyles, F., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Deane, Charlotte M.
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2021-10-29
- Volume
- 31
- Issue
- 1
- Pages
- 141-146
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- PMC
- PMC8740823
- OpenAlex
- W3206187363
- Cited by
- 319
- References
- 34
- Citations by year
- 2026: 65 · 2025: 112 · 2024: 77 · 2023: 45 · 2022: 19 · 2021: 1
- FWCI
- 18.74
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Protein Science (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/S024093/1)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- antibody repertoire, B cell receptor repertoire, sequence annotation, SARS-CoV-2 antibodies, immunogenomics, web server
- MeSH terms
- COVID-19, SARS-CoV-2, Amino Acid Sequence, Animals, Antibodies, Humans, Immunoglobulin Variable Region, Immunoglobulin Heavy Chains, Immunoglobulin Light Chains, Databases, Protein
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