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: 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

Need some help? Ask on the Bioconductor Support site!

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

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
Suggests Me
Links To Me
Build Report	Build Report

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/
Package Downloads Report	Download Stats