Package: ClustIRR 1.5.42

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_1.5.42.tar.gz
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ClustIRR_1.5.42.tgz(r-4.5-x86_64)ClustIRR_1.5.42.tgz(r-4.5-arm64)ClustIRR_1.5.42.tgz(r-4.4-x86_64)ClustIRR_1.5.42.tgz(r-4.4-arm64)ClustIRR_1.5.42.tgz(r-4.3-x86_64)ClustIRR_1.5.42.tgz(r-4.3-arm64)
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ClustIRR.pdf |ClustIRR.html
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' and 'D1' with TCRalphabeta mock repertoires
  • D1 - Datasets 'CDR3ab' and 'D1' 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-1.5.41(bioc 3.21)ClustIRR-1.4.0(bioc 3.20)

clusteringimmunooncologysinglecellsoftwareclassificationb-cell-receptorbioinformaticsimmunoinformaticsimmunologyquantitative-methodsrep-seqrepertoire-analysist-cell-receptorcpp

5.95 score 2 stars 2 scripts 196 downloads 13 exports 98 dependencies

Last updated 7 days agofrom:ee730f7234. Checks:1 OK, 10 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 01 2025
R-4.5-win-x86_64NOTEMar 01 2025
R-4.5-mac-x86_64NOTEMar 01 2025
R-4.5-mac-aarch64NOTEMar 01 2025
R-4.5-linux-x86_64NOTEMar 01 2025
R-4.4-win-x86_64NOTEMar 01 2025
R-4.4-mac-x86_64NOTEMar 01 2025
R-4.4-mac-aarch64NOTEMar 01 2025
R-4.3-win-x86_64NOTEMar 01 2025
R-4.3-mac-x86_64NOTEMar 01 2025
R-4.3-mac-aarch64NOTEMar 01 2025

Exports:cluster_irrdcodecode_communitiesdetect_communitiesget_ag_summaryget_beta_scatterplotget_beta_violinsget_clustirr_clustget_clustirr_inputsget_graphget_honeycombsget_joint_graphplot_graph

Dependencies:abindbackportsbase64encBHblasterbslibcachemcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionaldplyrevaluatefansifarverfastmapfontawesomefsfuturefuture.applygenericsggforceggplot2globalsgluegridExtragtablehighrhtmltoolshtmlwidgetsigraphinlineisobandjquerylibjsonliteknitrlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmenumDerivparallellypillarpkgbuildpkgconfigplyrpolyclipposteriorprocessxpspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrmarkdownrstanrstantoolssassscalesStanHeadersstringdiststringistringrsystemfontstensorAtibbletidyrtidyselecttinytextweenrutf8vctrsviridisLitevisNetworkwithrxfunyaml

Decoding T- and B-cell receptor repertoires with ClustIRR

Rendered fromUser_manual.Rmdusingknitr::rmarkdownon Mar 01 2025.

Last update: 2025-02-27
Started: 2023-05-22