ArticleBioinformatics (Oxford, England)2022
CompAIRR: ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026Article
- Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood.Science advances · 2026Article
- 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
- Predictability of antigen binding based on short motifs in the antibody CDRH3.Briefings in bioinformatics · 2024Article
- nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.PLoS computational biology · 2024Article
- Enhancing comparative T cell receptor repertoire analysis in small biological samples through pooling homologous cell samples from multiple mice.Cell reports methods · 2024Article
- Systems immunology spanning tumors, lymph nodes, and periphery.Cell reports methods · 2023Review
- KA-Search, a method for rapid and exhaustive sequence identity search of known antibodies.Scientific reports · 2023Article
- T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- simAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods.GigaScience · 2022Article
- AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses.PLoS computational biology · 2022Article
- Reference-based comparison of adaptive immune receptor repertoires.Cell reports methods · 2022Article
- Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification.GigaScience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
motivationAdaptive immune receptor (AIR) repertoires (AIRRs) record past immune encounters with exquisite specificity. Therefore, identifying identical or similar AIR sequences across individuals is a key step in AIRR analysis for revealing convergent immune response patterns that may be exploited for diagnostics and therapy. Existing methods for quantifying AIRR overlap scale poorly with increasing dataset numbers and sizes. To address this limitation, we developed CompAIRR, which enables ultra-fast computation of AIRR overlap, based on either exact or approximate sequence matching.
resultsCompAIRR improves computational speed 1000-fold relative to the state of the art and uses only one-third of the memory: on the same machine, the exact pairwise AIRR overlap of 104 AIRRs with 105 sequences is found in ∼17 min, while the fastest alternative tool requires 10 days. CompAIRR has been integrated with the machine learning ecosystem immuneML to speed up commonly used AIRR-based machine learning applications. AVAILABILITY AND IMPLEMENTATION: CompAIRR code and documentation are available at https://github.com/uio-bmi/compairr. Docker images are available at https://hub.docker.com/r/torognes/compairr. The code to replicate the synthetic datasets, scripts for benchmarking and creating figures, and all raw data underlying the figures are available at https://github.com/uio-bmi/compairr-benchmarking. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Indexed as
Identifiers
What OpenQuestion holds
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.