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scDataviz

scDataviz: single cell dataviz and downstream analyses


Bioconductor version: Release (3.18)

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 "4.3") and enter:


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

BiocManager::install("scDataviz")

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("scDataviz")
scDataviz: single cell dataviz and downstream analyses HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DataImport, FlowCytometry, GeneExpression, ImmunoOncology, MassSpectrometry, RNASeq, SingleCell, Software, Transcription
Version 1.12.0
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
See More
Suggests PCAtools, cowplot, BiocGenerics, RUnit, knitr, kableExtra, rmarkdown
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
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Package Archives

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

Source Package scDataviz_1.12.0.tar.gz
Windows Binary scDataviz_1.12.0.zip
macOS Binary (x86_64) scDataviz_1.12.0.tgz
macOS Binary (arm64) scDataviz_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/scDataviz
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scDataviz
Bioc Package Browser https://code.bioconductor.org/browse/scDataviz/
Package Short Url https://bioconductor.org/packages/scDataviz/
Package Downloads Report Download Stats