Method for identification of condition-associated public antigen receptor sequences
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
724208
European Research Council - International
PubMed
29533178
PubMed Central
PMC5873893
DOI
10.7554/elife.33050
PII: 33050
Knihovny.cz E-zdroje
- Klíčová slova
- computational biology, condition associated receptors, human, immunology, inflammation, repertoire sequencing, statistical analysis, systems biology,
- MeSH
- adaptivní imunita genetika MeSH
- Cytomegalovirus imunologie MeSH
- diabetes mellitus genetika imunologie MeSH
- genetická variace imunologie MeSH
- hypervariabilní oblasti genetika MeSH
- lidé MeSH
- receptory antigenů B-buněk genetika MeSH
- receptory antigenů T-buněk genetika imunologie MeSH
- receptory antigenů genetika imunologie MeSH
- receptory imunologické genetika imunologie MeSH
- vysoce účinné nukleotidové sekvenování MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- hypervariabilní oblasti MeSH
- receptory antigenů B-buněk MeSH
- receptory antigenů T-buněk MeSH
- receptory antigenů MeSH
- receptory imunologické MeSH
Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCR[Formula: see text] sequences .
Biological Faculty Moscow State University Moscow Russia
Central European Institute of Technology Brno Czech republic
Laboratoire de Physique Theorique CNRS Sorbonne University École Normale Supérieure Paris France
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