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scDataviz

scDataviz: single cell dataviz and downstream analyses

Bioconductor version: 3.23 · Package version: 1.22.0

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.

Installation

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

BiocManager::install("scDataviz")

Details

MaintainerKevin Blighe <kevin@clinicalbioinformatics.co.uk>
AuthorKevin Blighe [aut, cre]
LicenseGPL-3
URLhttps://github.com/kevinblighe/scDataviz
Bug Reportshttps://github.com/kevinblighe/scDataviz/issues
Downloads rank279
Source branchRELEASE_3_23
biocViewsDataImport, FlowCytometry, GeneExpression, ImmunoOncology, MassSpectrometry, RNASeq, SingleCell, Software, Transcription

Documentation

Download

Dependencies

Depends: R (>= 4.0), S4Vectors, SingleCellExperiment

Imports: ggplot2, ggrepel, flowCore, umap, Seurat, reshape2, scales, RColorBrewer, corrplot, stats, grDevices, graphics, utils, MASS, matrixStats, methods

Suggests: PCAtools, cowplot, BiocGenerics, RUnit, knitr, kableExtra, rmarkdown