Package: ClustIRR 1.5.24

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_1.5.24.tar.gz
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ClustIRR_1.5.24.tgz(r-4.4-x86_64)ClustIRR_1.5.24.tgz(r-4.4-arm64)ClustIRR_1.5.24.tgz(r-4.3-x86_64)ClustIRR_1.5.24.tgz(r-4.3-arm64)
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ClustIRR_1.3.24.tgz(r-4.4-emscripten)ClustIRR_1.3.24.tgz(r-4.3-emscripten)
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'))

Peer review:

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

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • BLOSUM62 - BLOSUM62 matrix
  • CDR3ab - Mock data set of complementarity determining region 3 (CDR3) sequences from the alpha and beta chains of 10,000 T cell receptors
  • 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-1.5.19(bioc 3.21)ClustIRR-1.4.0(bioc 3.20)

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

5.94 score 2 stars 2 scripts 142 downloads 8 exports 90 dependencies

Last updated 23 hours agofrom:132e5b9659. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 22 2024
R-4.5-win-x86_64NOTEDec 22 2024
R-4.5-linux-x86_64NOTEDec 22 2024
R-4.4-win-x86_64NOTEDec 22 2024
R-4.4-mac-x86_64NOTEDec 22 2024
R-4.4-mac-aarch64NOTEDec 22 2024
R-4.3-win-x86_64NOTEDec 22 2024
R-4.3-mac-x86_64NOTEDec 22 2024
R-4.3-mac-aarch64NOTEDec 22 2024

Exports:cluster_irrdcodetect_communitiesget_clustirr_clustget_clustirr_inputsget_graphget_joint_graphplot_graph

Dependencies:abindbackportsbase64encBHblasterbslibcachemcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionalevaluatefansifarverfastmapfontawesomefsfuturefuture.applygenericsggplot2globalsgluegridExtragtablehighrhtmltoolshtmlwidgetsigraphinlineisobandjquerylibjsonliteknitrlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpsQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrmarkdownrstanrstantoolssassscalesStanHeadersstringdiststringistringrtensorAtibbletinytexutf8vctrsviridisLitevisNetworkwithrxfunyaml

Analysis of T and B cell receptor repertoires with ClustIRR

Rendered fromUser_manual.Rmdusingknitr::rmarkdownon Dec 22 2024.

Last update: 2024-12-03
Started: 2023-05-22