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>

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

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
Package Short Url https://bioconductor.org/packages/cardelino/
Package Downloads Report Download Stats

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