Package: scRepertoire 2.1.0

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'))

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

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

contig_list - A list of 8 single-cell T cell receptor sequences runs.
mini_contig_list - Processed subset of 'contig_list'
scRep_example - A Seurat object of 500 single T cells,

On BioConductor:scRepertoire-2.1.0(bioc 3.20)scRepertoire-2.0.0(bioc 3.19)

bioconductor-package

35 exports 1.31 score 110 dependencies 3 mentions

Last updated 2 months agofrom:9061c35380

Exports:addVariable alluvialClones clonalAbundance clonalBias clonalCluster clonalCompare clonalDiversity clonalHomeostasis clonalLength clonalNetwork clonalOccupy clonalOverlap clonalOverlay clonalProportion clonalQuant clonalRarefaction clonalScatter clonalSizeDistribution combineBCR combineExpression combineTCR createHTOContigList exportClones getCirclize highlightClones loadContigs percentAA percentGenes percentKmer percentVJ positionalEntropy positionalProperty StartracDiversity subsetClones vizGenes

Dependencies:abind askpass Biobase BiocGenerics cachem cli codetools colorspace cpp11 crayon cubature curl DelayedArray digest dotCall64 dplyr evd evmix fansi farver fastmap future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggalluvial ggdendro ggforce ggplot2 ggraph ggrepel globals glue graphlayouts gridExtra gsl gtable hash httr igraph iNEXT IRanges isoband jsonlite labeling lattice lazyeval lifecycle listenv magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats memoise mgcv mime munsell nlme openssl parallelly pillar pkgconfig plyr polyclip progressr purrr quantreg R6 RColorBrewer Rcpp RcppArmadillo RcppEigen reshape2 rjson rlang S4Arrays S4Vectors scales SeuratObject SingleCellExperiment sp spam SparseArray SparseM stringdist stringi stringr SummarizedExperiment survival sys systemfonts tibble tidygraph tidyr tidyselect truncdist tweenr UCSC.utils utf8 vctrs VGAM viridis viridisLite withr XVector zlibbioc

Starting work with scRepertoire.

Nick Borcherding

Rendered fromvignette.Rmdusingknitr::rmarkdownon Jun 30 2024.

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Adding variables after combineTCR() or combineBCR()	addVariable
Alluvial plotting for single-cell object meta data	alluvialClones
Demonstrate the relative abundance of clones by group or sample	clonalAbundance
Examine skew of clones towards a cluster or compartment	clonalBias
Clustering adaptive receptor sequences by edit distance	clonalCluster
Demonstrate the difference in clonal proportion between clones	clonalCompare
Calculate the clonal diversity for samples or groupings	clonalDiversity
Examining the clonal homeostasis of the repertoire	clonalHomeostasis
Demonstrate the distribution of clonal length	clonalLength
Visualize clonal network along reduced dimensions	clonalNetwork
Visualize the number of single cells with cloneSizes by cluster	clonalOccupy
Examining the clonal overlap between groups or samples	clonalOverlap
Visualize distribution of clonal frequency overlaid on dimensional reduction plots	clonalOverlay
Examining the clonal space occupied by specific clones	clonalProportion
Quantify the unique clones by group or sample	clonalQuant
Calculate rarefaction based on the abundance of clones	clonalRarefaction
Scatter plot comparing the clonal expansion of two samples	clonalScatter
Hierarchical clustering of clones using Gamma-GPD spliced threshold model	clonalSizeDistribution
Combining the list of B cell receptor contigs into clones	combineBCR
Adding clone information to a single-cell object	combineExpression
Combining the list of T cell receptor contigs into clones	combineTCR
A list of 8 single-cell T cell receptor sequences runs.	contig_list
Generate a contig list from a multiplexed experiment	createHTOContigList
Exporting clones	exportClones
Generate data frame to be used with circlize R package to visualize clones as a chord diagram.	getCirclize
Highlighting specific clones in Seurat	highlightClones
Loading the contigs derived from single-cell sequencing	loadContigs
Processed subset of `contig_list`	mini_contig_list
Examining the relative amino acid composition by position	percentAA
Examining the VDJ gene usage across clones	percentGenes
Examining the relative composition of kmer motifs in clones.	percentKmer
Quantifying the V and J gene usage across clones	percentVJ
Examining the diversity of amino acids by position	positionalEntropy
Examining the mean property of amino acids by position	positionalProperty
A Seurat object of 500 single T cells,	scRep_example
Startrac-based diversity indices for single-cell RNA-seq	StartracDiversity
Subset the product of combineTCR() or combineBCR()	subsetClones
Visualizing the distribution of gene usage	vizGenes