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scBubbletree

Quantitative visual exploration of scRNA-seq data

Bioconductor version: 3.23 · Package version: 1.14.0

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.

Installation

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

BiocManager::install("scBubbletree")

Details

MaintainerSimo Kitanovski <simokitanovski@gmail.com>
AuthorSimo Kitanovski [aut, cre]
LicenseGPL-3 + file LICENSE
URLhttps://github.com/snaketron/scBubbletree
Bug Reportshttps://github.com/snaketron/scBubbletree/issues
System RequirementsPython (>= 3.6), leidenalg (>= 0.8.2)
Downloads rank236
Source branchRELEASE_3_23
biocViewsClustering, RNASeq, SingleCell, Software, Transcriptomics, Visualization

Documentation

Download

Dependencies

Depends: R (>= 4.2.0)

Imports: reshape2, BiocParallel, ape, scales, Seurat, ggplot2, ggtree, patchwork, proxy, methods, stats, base, utils, dplyr

Suggests: BiocStyle, knitr, testthat, cluster, SingleCellExperiment