cardelino

This is the released version of cardelino; for the devel version, see cardelino.

Clone Identification from Single Cell Data


Bioconductor version: Release (3.20)

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], Yuanhua Huang [aut], Davis McCarthy [aut, cre]

Maintainer: Davis McCarthy <dmccarthy at svi.edu.au>

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

Installation

To install this package, start R (version "4.4") 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")
Clone ID with cardelino HTML R Script
Reference Manual PDF

Details

biocViews ExomeSeq, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcriptomics, Visualization
Version 1.8.0
In Bioconductor since BioC 3.16 (R-4.2) (2 years)
License GPL-3
Depends R (>= 4.2), stats
Imports combinat, GenomeInfoDb, GenomicRanges, ggplot2, ggtree, Matrix, matrixStats, methods, pheatmap, snpStats, S4Vectors, utils, VariantAnnotation, vcfR
System Requirements
URL https://github.com/single-cell-genetics/cardelino
Bug Reports https://github.com/single-cell-genetics/cardelino/issues
See More
Suggests BiocStyle, foreach, knitr, pcaMethods, rmarkdown, testthat, VGAM
Linking To
Enhances doMC
Depends On Me
Imports Me
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Package Archives

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

Source Package cardelino_1.8.0.tar.gz
Windows Binary (x86_64) cardelino_1.8.0.zip
macOS Binary (x86_64) cardelino_1.8.0.tgz
macOS Binary (arm64) cardelino_1.8.0.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