Package: ClustIRR 1.11.0

Simo Kitanovski

ClustIRR: Clustering of Immune Receptor Repertoires

ClustIRR analyzes repertoires of B- and T-cell receptors. It starts by identifying communities of immune receptors with similar specificities, based on the sequences of their complementarity-determining regions (CDRs). Next, it employs a Bayesian probabilistic models to quantify differential community occupancy (DCO) between repertoires, allowing the identification of expanding or contracting communities in response to e.g. infection or cancer treatment.

Authors:Simo Kitanovski [aut, cre], Kai Wollek [aut]

ClustIRR_1.11.0.tar.gz
ClustIRR_1.11.0.zip(r-4.7)ClustIRR_1.11.0.zip(r-4.6)ClustIRR_1.11.0.zip(r-4.5)
ClustIRR_1.11.0.tgz(r-4.6-x86_64)ClustIRR_1.11.0.tgz(r-4.6-arm64)ClustIRR_1.11.0.tgz(r-4.5-x86_64)ClustIRR_1.11.0.tgz(r-4.5-arm64)
ClustIRR_1.11.0.tar.gz(r-4.7-arm64)ClustIRR_1.11.0.tar.gz(r-4.7-x86_64)ClustIRR_1.11.0.tar.gz(r-4.6-arm64)ClustIRR_1.11.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
ClustIRR/json (API)
NEWS

# Install 'ClustIRR' in R:

install.packages('ClustIRR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/snaketron/clustirr/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

BLOSUM62 - BLOSUM62 matrix
CDR3ab - Datasets 'CDR3ab', 'D1' and 'D2' with TCRalphabeta mock repertoires
D1 - Datasets 'CDR3ab', 'D1' and 'D2' with TCRalphabeta mock repertoires
D2 - Datasets 'CDR3ab', 'D1' and 'D2' with TCRalphabeta mock repertoires
mcpas - CDR3 sequences and their matching epitopes obtained from McPAS-TCR
tcr3d - CDR3 sequences and their matching epitopes obtained from TCR3d
vdjdb - CDR3 sequences and their matching epitopes obtained from VDJdb

On BioConductor:ClustIRR-1.11.0(bioc 3.24)ClustIRR-1.10.0(bioc 3.23)

clustering immunooncology singlecell software classification bayesian biomedicalinformatics mathematicalbiology b-cell-receptor bioinformatics immunoinformatics immunology quantitative-methods rep-seq repertoire-analysis t-cell-receptor cpp

6.36 score 5 stars 11 scripts 278 downloads 19 exports 112 dependencies

Last updated from:2fea7dd47b. Checks:12 NOTE, 1 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	246
linux-devel-arm64	NOTE	407
linux-devel-x86_64	NOTE	464
source / vignettes	OK	446
linux-release-arm64	NOTE	380
linux-release-x86_64	NOTE	426
macos-release-arm64	NOTE	254
macos-release-x86_64	NOTE	536
macos-oldrel-arm64	NOTE	221
macos-oldrel-x86_64	NOTE	463
windows-devel	NOTE	719
windows-release	NOTE	392
windows-oldrel	NOTE	665
wasm-release	FAIL	158

Exports:clustirr dco decode_all_communities decode_community detect_communities get_ag_gene_hits get_ag_species_hits get_beta_cprob_ag get_beta_violin_ag get_cdr3_motifs get_clustirr_clust get_clustirr_inputs get_community_feature_purity get_community_feature_stats get_cosine_similarity get_honeycombs get_nrads plot_graph save_interactive_graph

Dependencies:abind askpass backports base64enc BH BiocFileCache BiocGenerics Biostrings bit bit64 blob bslib cachem callr checkmate cli cpp11 crayon curl DBI dbplyr desc digest distributional dplyr evaluate farver fastmap filelock fontawesome fs generics ggforce ggplot2 ggseqlogo glue gridExtra gtable highr htmltools htmlwidgets httr2 igraph inline IRanges isoband jquerylib jsonlite knitr labeling lattice lifecycle loo magrittr MASS Matrix matrixStats memoise mime msa numDeriv openssl pillar pkgbuild pkgconfig plyr polyclip posterior processx ps purrr QuickJSR R6 RADanalysis rappdirs rBLAST RColorBrewer Rcpp RcppEigen RcppParallel reshape2 rlang rmarkdown RSQLite rstan rstantools S4Vectors S7 sass scales Seqinfo sfsmisc StanHeaders stringdist stringi stringr sys systemfonts tensorA tibble tidyr tidyselect tinytex tweenr utf8 vctrs viridisLite visNetwork withr xfun XVector yaml

Decoding T- and B-cell receptor repertoires with ClustIRR

Rendered fromUser_manual_introduction.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2026-04-10
Started: 2026-01-05

Finding biological condition-specific changes in T- and B-cell receptor repertoires with ClustIRR

Rendered fromUser_manual_groups.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2026-04-09
Started: 2026-01-05

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
BLOSUM62 matrix	BLOSUM62
clust_irr class	class:clust_irr clust_irr clust_irr-class get_clustirr_clust get_clustirr_clust,clust_irr-method get_clustirr_inputs get_clustirr_inputs,clust_irr-method
Clustering of immune receptor repertoires (IRRs)	clustirr
Datasets 'CDR3ab', 'D1' and 'D2' with TCRalphabeta mock repertoires	CDR3ab D1 D2
Model-based differential community occupancy (DCO) analysis	dco
Decode all graph communities	decode_all_communities
Decode graph communities	decode_community
Graph-based community detection (GCD)	detect_communities
Annotate antigen gene hits in node summary	get_ag_gene_hits
Annotate antigen species hits in node summary	get_ag_species_hits
Visualize cumulative probability of beta means for antigen-specific communities	get_beta_cprob_ag
Visualize distribution of beta means in each repertoire as violin plots	get_beta_violin_ag
Generate CDR3 motif for communities	get_cdr3_motifs
Compute community purity with respect to a node feature	get_community_feature_purity
Compute descriptive statistics of a community node feature	get_community_feature_stats
Compute and Visualize Cosine Similarity (CS)	get_cosine_similarity
Generate honycomb plot: visualize community occupancy of pairs of immune receptor repertoires	get_honeycombs
Compute Normalized Rank Abundance Distributions (NRADs)	get_nrads
CDR3 sequences and their matching epitopes obtained from McPAS-TCR	mcpas
Plot ClustIRR graph	plot_graph
Save interactive ClustIRR graph	save_interactive_graph
CDR3 sequences and their matching epitopes obtained from TCR3d	tcr3d
CDR3 sequences and their matching epitopes obtained from VDJdb	vdjdb