scBubbletree

This is the development version of scBubbletree; for the stable release version, see scBubbletree.

Quantitative visual exploration of scRNA-seq data


Bioconductor version: Development (3.20)

scBubbletree is a quantitative method for the visual exploration of scRNA-seq data, preserving key biological properties such as local and global cell distances and cell density distributions across samples. It effectively resolves overplotting and enables the visualization of diverse cell attributes from multiomic single-cell experiments. Additionally, scBubbletree is user-friendly and integrates seamlessly with popular scRNA-seq analysis tools, facilitating comprehensive and intuitive data interpretation.

Author: Simo Kitanovski [aut, cre]

Maintainer: Simo Kitanovski <simokitanovski at gmail.com>

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

Installation

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


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scBubbletree")

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("scBubbletree")
User Manual: scBubbletree HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Clustering, RNASeq, SingleCell, Software, Transcriptomics, Visualization
Version 1.7.23
In Bioconductor since BioC 3.16 (R-4.2) (2 years)
License GPL-3 + file LICENSE
Depends R (>= 4.2.0)
Imports reshape2, BiocParallel, ape, scales, Seurat, ggplot2, ggtree, patchwork, proxy, methods, stats, base, utils, dplyr
System Requirements Python (>= 3.6), leidenalg (>= 0.8.2)
URL https://github.com/snaketron/scBubbletree
Bug Reports https://github.com/snaketron/scBubbletree/issues
See More
Suggests BiocStyle, knitr, testthat, cluster, SingleCellExperiment
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Package Archives

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

Source Package scBubbletree_1.7.23.tar.gz
Windows Binary (x86_64) scBubbletree_1.7.23.zip
macOS Binary (x86_64) scBubbletree_1.7.23.tgz
macOS Binary (arm64) scBubbletree_1.7.23.tgz
Source Repository git clone https://git.bioconductor.org/packages/scBubbletree
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scBubbletree
Bioc Package Browser https://code.bioconductor.org/browse/scBubbletree/
Package Short Url https://bioconductor.org/packages/scBubbletree/
Package Downloads Report Download Stats