ReviewImmunological reviews2018
Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination.
Review in Immunological reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
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Who cites it
82 citing papers in PubMed.
- Azacitidine-induced reconstitution of the bone marrow T cell repertoire is associated with superior survival in AML patients.Blood cancer journal · 2022Trial
- T-cell receptor repertoires as potential diagnostic markers for patients with COVID-19.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021Trial
- Heart-specific T cell responses: from antigens to disease mechanisms.Nature reviews. Cardiology · 2026Review
- Exploration of immune correlates of viral clearance after PVX2 immunotherapy in patients with human papillomavirus type 16 infection and cervical intraepithelial neoplasia grade ≤1.Journal of virology · 2026Article
- Machine Learning of Personal Repertoires From Public T Cell Receptors.Immunological reviews · 2026Review
- T-cell repertoire response in individuals with post-acute sequelae of COVID-19.bioRxiv : the preprint server for biology · 2026Article
- Analysis of the TCRβ repertoire characteristics when combining radiotherapy and immunotherapy in cancer.Oncology letters · 2026Article
- TCR2HLA: Calibrated inference of HLA genotypes from TCR repertoires enables identification of immunologically relevant metaclonotypes.PLoS computational biology · 2026Article
- T Cell Receptor Sharing in Hypersensitivity Pneumonitis.Computational and structural biotechnology journal · 2026Article
- Genetic and environmental imprints on T cell receptor repertoires as predictors of graft-versus-host disease.bioRxiv : the preprint server for biology · 2025Article
- Identification of Sjögren's disease-associated T cell receptor motifs through deep sequencing.JCI insight · 2025Article
- A pan-disease and population-level single-cell TCRαβ repertoire reference.Cell discovery · 2025Article
- SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES.The annals of applied statistics · 2025Article
- Neighborhood enrichment for the identification of antigen-specific T-cell receptors.Briefings in bioinformatics · 2025Article
- TCR2HLA: calibrated inference of HLA genotypes from TCR repertoires enables identification of immunologically relevant metaclonotypes.bioRxiv : the preprint server for biology · 2025Article
- Statistical analysis of repertoire data demonstrates the influence of microhomology in V(D)J recombination.Nucleic acids research · 2025Article
- Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning.Nucleic acids research · 2025Article
- Single-cell analysis of cerebrospinal fluid reveals common features of neuroinflammation.Cell reports. Medicine · 2025Article
- Learning predictive signatures of HLA type from T-cell repertoires.PLoS computational biology · 2025Article
- A general pHLA-CD80 scaffold fusion protein to promote efficient antigen-specific T cell-based immunotherapy.Molecular therapy. Oncology · 2024Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the extreme diversity of T-cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely shared sequences, often referred to as "public," have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here, we show that even for large cohorts, the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations, we propose a public/private sequence classifier, "PUBLIC" (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.
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Registered trials
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.