Package: scRepertoire 2.3.0

Nick Borcherding

scRepertoire: A toolkit for single-cell immune receptor profiling

scRepertoire is a toolkit for processing and analyzing single-cell T-cell receptor (TCR) and immunoglobulin (Ig). The scRepertoire framework supports use of 10x, AIRR, BD, MiXCR, Omniscope, TRUST4, and WAT3R single-cell formats. The functionality includes basic clonal analyses, repertoire summaries, distance-based clustering and interaction with the popular Seurat and SingleCellExperiment/Bioconductor R workflows.

Authors:Nick Borcherding [aut, cre], Qile Yang [aut], Ksenia Safina [aut]

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scRepertoire.pdf |scRepertoire.html✨
scRepertoire/json (API)
NEWS

# Install 'scRepertoire' in R:
install.packages('scRepertoire', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ncborcherding/screpertoire/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:scRepertoire-2.3.0(bioc 3.21)scRepertoire-2.2.0(bioc 3.20)

softwareimmunooncologysinglecellclassificationannotationsequencing

9.69 score 308 stars 202 scripts 928 downloads 3 mentions 35 exports 110 dependencies

Last updated 23 days agofrom:a2ba28bf19. Checks:OK: 2 NOTE: 2 WARNING: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64WARNINGOct 31 2024
R-4.5-linux-x86_64NOTEOct 31 2024
R-4.4-win-x86_64WARNINGOct 31 2024
R-4.4-mac-x86_64WARNINGOct 31 2024
R-4.4-mac-aarch64NOTEOct 31 2024
R-4.3-win-x86_64WARNINGOct 31 2024
R-4.3-mac-x86_64WARNINGOct 31 2024
R-4.3-mac-aarch64OKOct 31 2024

Exports:addVariablealluvialClonesclonalAbundanceclonalBiasclonalClusterclonalCompareclonalDiversityclonalHomeostasisclonalLengthclonalNetworkclonalOccupyclonalOverlapclonalOverlayclonalProportionclonalQuantclonalRarefactionclonalScatterclonalSizeDistributioncombineBCRcombineExpressioncombineTCRcreateHTOContigListexportClonesgetCirclizehighlightClonesloadContigspercentAApercentGenespercentKmerpercentVJpositionalEntropypositionalPropertyStartracDiversitysubsetClonesvizGenes

Dependencies:abindaskpassBiobaseBiocGenericscachemclicodetoolscolorspacecpp11crayoncubaturecurlDelayedArraydigestdotCall64dplyrevdevmixfansifarverfastmapfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggalluvialggdendroggforceggplot2ggraphggrepelglobalsgluegraphlayoutsgridExtragslgtablehashhttrigraphiNEXTIRangesisobandjsonlitelabelinglatticelazyevallifecyclelistenvmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmimemunsellnlmeopensslparallellypillarpkgconfigplyrpolyclipprogressrpurrrquantregR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rjsonrlangS4ArraysS4VectorsscalesSeuratObjectSingleCellExperimentspspamSparseArraySparseMstringdiststringistringrSummarizedExperimentsurvivalsyssystemfontstibbletidygraphtidyrtidyselecttruncdisttweenrUCSC.utilsutf8vctrsVGAMviridisviridisLitewithrXVectorzlibbioc

Starting work with scRepertoire.

Nick Borcherding

Rendered fromvignette.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2024-03-04
Started: 2020-01-18

Readme and manuals

Help Manual

Help pageTopics
Adding variables after combineTCR() or combineBCR()addVariable
Alluvial plotting for single-cell object meta dataalluvialClones
Demonstrate the relative abundance of clones by group or sampleclonalAbundance
Examine skew of clones towards a cluster or compartmentclonalBias
Clustering adaptive receptor sequences by edit distanceclonalCluster
Demonstrate the difference in clonal proportion between clonesclonalCompare
Calculate the clonal diversity for samples or groupingsclonalDiversity
Examining the clonal homeostasis of the repertoireclonalHomeostasis
Demonstrate the distribution of clonal lengthclonalLength
Visualize clonal network along reduced dimensionsclonalNetwork
Visualize the number of single cells with cloneSizes by clusterclonalOccupy
Examining the clonal overlap between groups or samplesclonalOverlap
Visualize distribution of clonal frequency overlaid on dimensional reduction plotsclonalOverlay
Examining the clonal space occupied by specific clonesclonalProportion
Quantify the unique clones by group or sampleclonalQuant
Calculate rarefaction based on the abundance of clonesclonalRarefaction
Scatter plot comparing the clonal expansion of two samplesclonalScatter
Hierarchical clustering of clones using Gamma-GPD spliced threshold modelclonalSizeDistribution
Combining the list of B cell receptor contigs into clonescombineBCR
Adding clone information to a single-cell objectcombineExpression
Combining the list of T cell receptor contigs into clonescombineTCR
A list of 8 single-cell T cell receptor sequences runs.contig_list
Generate a contig list from a multiplexed experimentcreateHTOContigList
Exporting clonesexportClones
Generate data frame to be used with circlize R package to visualize clones as a chord diagram.getCirclize
Highlighting specific clones in SeurathighlightClones
Loading the contigs derived from single-cell sequencingloadContigs
Processed subset of `contig_list`mini_contig_list
Examining the relative amino acid composition by positionpercentAA
Examining the VDJ gene usage across clonespercentGenes
Examining the relative composition of kmer motifs in clones.percentKmer
Quantifying the V and J gene usage across clonespercentVJ
Examining the diversity of amino acids by positionpositionalEntropy
Examining the mean property of amino acids by positionpositionalProperty
A Seurat object of 500 single T cells,scRep_example
Startrac-based diversity indices for single-cell RNA-seqStartracDiversity
Subset the product of combineTCR() or combineBCR()subsetClones
Visualizing the distribution of gene usagevizGenes