scDataviz

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

scDataviz: single cell dataviz and downstream analyses

Bioconductor version: Development (3.19)

In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.

Author: Kevin Blighe [aut, cre]

Maintainer: Kevin Blighe <kevin at clinicalbioinformatics.co.uk>

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

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("scDataviz")

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

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DataImport, FlowCytometry, GeneExpression, ImmunoOncology, MassSpectrometry, RNASeq, SingleCell, Software, Transcription
Version	1.13.0
In Bioconductor since	BioC 3.12 (R-4.0) (3.5 years)
License	GPL-3
Depends	R (>= 4.0), S4Vectors, SingleCellExperiment
Imports	ggplot2, ggrepel, flowCore, umap, Seurat, reshape2, scales, RColorBrewer, corrplot, stats, grDevices, graphics, utils, MASS, matrixStats, methods
System Requirements
URL	https://github.com/kevinblighe/scDataviz
Bug Reports	https://github.com/kevinblighe/scDataviz/issues

Suggests	PCAtools, cowplot, BiocGenerics, RUnit, knitr, kableExtra, rmarkdown
Linking To
Enhances
Depends On Me
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Build Report	Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/scDataviz
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/scDataviz
Package Short Url	https://bioconductor.org/packages/scDataviz/
Package Downloads Report	Download Stats