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:
ClustIRR_1.5.24.tar.gz
ClustIRR_1.5.24.zip(r-4.5)ClustIRR_1.5.24.zip(r-4.4)ClustIRR_1.5.24.zip(r-4.3)
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)
ClustIRR_1.5.24.tar.gz(r-4.5-noble)ClustIRR_1.5.24.tar.gz(r-4.4-noble)
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')) |
Bug tracker:https://github.com/snaketron/clustirr/issues
- 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
Last updated 23 hours agofrom:132e5b9659. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 22 2024 |
R-4.5-win-x86_64 | NOTE | Dec 22 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 22 2024 |
R-4.4-win-x86_64 | NOTE | Dec 22 2024 |
R-4.4-mac-x86_64 | NOTE | Dec 22 2024 |
R-4.4-mac-aarch64 | NOTE | Dec 22 2024 |
R-4.3-win-x86_64 | NOTE | Dec 22 2024 |
R-4.3-mac-x86_64 | NOTE | Dec 22 2024 |
R-4.3-mac-aarch64 | NOTE | Dec 22 2024 |
Exports:cluster_irrdcodetect_communitiesget_clustirr_clustget_clustirr_inputsget_graphget_joint_graphplot_graph
Dependencies:abindbackportsbase64encBHblasterbslibcachemcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionalevaluatefansifarverfastmapfontawesomefsfuturefuture.applygenericsggplot2globalsgluegridExtragtablehighrhtmltoolshtmlwidgetsigraphinlineisobandjquerylibjsonliteknitrlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpsQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrmarkdownrstanrstantoolssassscalesStanHeadersstringdiststringistringrtensorAtibbletinytexutf8vctrsviridisLitevisNetworkwithrxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
BLOSUM62 matrix | BLOSUM62 |
Mock data set of complementarity determining region 3 (CDR3) sequences from the alpha and beta chains of 10,000 T cell receptors | CDR3ab |
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) | cluster_irr |
Model-based differential community occupancy (DCO) analysis | dco |
Graph-based community detection (GCD) | detect_communities |
Get 'igraph' object from 'clust_irr' object | get_graph |
Create joint 'igraph' object from multiple 'clust_irr' objects | get_joint_graph |
CDR3 sequences and their matching epitopes obtained from McPAS-TCR | mcpas |
Plot ClustIRR graph | plot_graph |
CDR3 sequences and their matching epitopes obtained from TCR3d | tcr3d |
CDR3 sequences and their matching epitopes obtained from VDJdb | vdjdb |