This is the development version of scDataviz; for the stable release version, see scDataviz.
scDataviz: single cell dataviz and downstream analysesBioconductor version: Development (3.22)
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, entercitation("scDataviz")): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("scDataviz")Follow Installation instructions to use this package in your R session.
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