CellaRepertorium

This package is for version 3.19 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see CellaRepertorium.

Data structures, clustering and testing for single cell immune receptor repertoires (scRNAseq RepSeq/AIRR-seq)


Bioconductor version: Release (3.19)

Methods to cluster and analyze high-throughput single cell immune cell repertoires, especially from the 10X Genomics VDJ solution. Contains an R interface to CD-HIT (Li and Godzik 2006). Methods to visualize and analyze paired heavy-light chain data. Tests for specific expansion, as well as omnibus oligoclonality under hypergeometric models.

Author: Andrew McDavid [aut, cre], Yu Gu [aut], Erik VonKaenel [aut], Aaron Wagner [aut], Thomas Lin Pedersen [ctb]

Maintainer: Andrew McDavid <Andrew_McDavid at urmc.rochester.edu>

Citation (from within R, enter citation("CellaRepertorium")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CellaRepertorium")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Clustering, ImmunoOncology, RNASeq, SingleCell, Software, TargetedResequencing, Technology, Transcriptomics
Version 1.14.0
In Bioconductor since BioC 3.12 (R-4.0) (4 years)
License GPL-3
Depends R (>= 4.0)
Imports dplyr, tibble, stringr, Biostrings, Rcpp, reshape2, methods, rlang (>= 0.3), purrr, Matrix, S4Vectors, BiocGenerics, tidyr, forcats, progress, stats, utils, generics, glue
System Requirements
URL https://github.com/amcdavid/CellaRepertorium
Bug Reports https://github.com/amcdavid/CellaRepertorium/issues
See More
Suggests testthat, readr, knitr, rmarkdown, ggplot2, BiocStyle, ggdendro, broom, lme4, RColorBrewer, SingleCellExperiment, scater, broom.mixed, cowplot, igraph, ggraph
Linking To Rcpp
Enhances
Depends On Me
Imports Me
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/CellaRepertorium
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CellaRepertorium
Package Short Url https://bioconductor.org/packages/CellaRepertorium/
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