ArticleNature communications2018
High-throughput immune repertoire analysis with IGoR.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 159 papers.
What it found
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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.
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.
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Who cites it
159 citing papers in PubMed.
- Trial
- Thymic selection of the T cell receptor repertoire is biased toward autoimmunity in females.eLife · 2026Article
- Machine Learning of Personal Repertoires From Public T Cell Receptors.Immunological reviews · 2026Review
- What Do Generative Models Learn About Adaptive Immune Receptor Repertoires? A Benchmark Study.bioRxiv : the preprint server for biology · 2026Article
- VDJ-REMIX: REpertoire Module Identification and eXploration.Bioinformatics (Oxford, England) · 2026Article
- T-cell repertoire response in individuals with post-acute sequelae of COVID-19.bioRxiv : the preprint server for biology · 2026Article
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- Deciphering antigen-driven T cell responses through vectorized TCRdist sequence neighborhood quantification.bioRxiv : the preprint server for biology · 2026Article
- Large-scale paired chain BCR analysis reveals antibody clonal family inference bias and enhances resolution with machine learning.PLoS computational biology · 2026Article
- Decoding adaptive immunity: advanced strategies in T and B cell repertoire analysis.Journal of translational medicine · 2026Review
- Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood.Science advances · 2026Article
- TCR representation learning with protein language models: a comprehensive review.International immunology · 2026Review
- TCR2HLA: Calibrated inference of HLA genotypes from TCR repertoires enables identification of immunologically relevant metaclonotypes.PLoS computational biology · 2026Article
- ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains.Nature methods · 2026Article
- Genetic and environmental imprints on T cell receptor repertoires as predictors of graft-versus-host disease.bioRxiv : the preprint server for biology · 2025Article
- Exploring coding and signal joints of novel TCR beta D-D rearrangements for tracking T-cell leukemia clonality.Experimental hematology & oncology · 2025Article
- Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025Article
- Neighborhood enrichment for the identification of antigen-specific T-cell receptors.Briefings in bioinformatics · 2025Article
- Article
- Divergent B-cell repertoire remodelling by mRNA, DNA and live attenuated vaccines in fish.NPJ vaccines · 2025Article
99 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)-a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can be used to investigate models of increasing biological complexity for different organisms. For B cells, IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.
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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.