cardelino

DOI: 10.18129/B9.bioc.cardelino  

Clone Identification from Single Cell Data

Bioconductor version: Release (3.16)

Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.

Author: Jeffrey Pullin [aut, cre], Yuanhua Huang [aut], Davis McCarthy [aut]

Maintainer: Jeffrey Pullin <jpullin at svi.edu.au>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("cardelino")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("cardelino")

 

HTML	R Script	Clone ID with cardelino
PDF		Reference Manual

Details

biocViews	ExomeSeq, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcriptomics, Visualization
Version	1.0.0
In Bioconductor since	BioC 3.16 (R-4.2) (< 6 months)
License	GPL-3
Depends	R (>= 4.2), stats
Imports	combinat, GenomeInfoDb, GenomicRanges, ggplot2, ggtree, Matrix, matrixStats, methods, pheatmap, snpStats, S4Vectors, utils, VariantAnnotation, vcfR
LinkingTo
Suggests	BiocStyle, foreach, knitr, pcaMethods, rmarkdown, testthat, VGAM
SystemRequirements
Enhances	doMC
URL	https://github.com/single-cell-genetics/cardelino
BugReports	https://github.com/single-cell-genetics/cardelino/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	cardelino_1.0.0.tar.gz
Windows Binary	cardelino_1.0.0.zip
macOS Binary (x86_64)	cardelino_1.0.0.tgz
macOS Binary (arm64)	cardelino_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/cardelino
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/cardelino
Bioc Package Browser	https://code.bioconductor.org/browse/cardelino/
Package Short Url	https://bioconductor.org/packages/cardelino/
Package Downloads Report	Download Stats