Package: scDataviz 1.23.0

Kevin Blighe

scDataviz: scDataviz: single cell dataviz and downstream analyses

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.

Authors:Kevin Blighe [aut, cre]

scDataviz_1.23.0.tar.gz
scDataviz_1.23.0.zip(r-4.7)scDataviz_1.23.0.zip(r-4.6)scDataviz_1.23.0.zip(r-4.5)
scDataviz_1.23.0.tgz(r-4.6-any)scDataviz_1.23.0.tgz(r-4.5-any)
scDataviz_1.23.0.tar.gz(r-4.7-any)scDataviz_1.23.0.tar.gz(r-4.6-any)
scDataviz_1.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scDataviz/json (API)
NEWS

# Install 'scDataviz' in R:
install.packages('scDataviz', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kevinblighe/scdataviz/issues

On BioConductor:scDataviz-1.23.0(bioc 3.24)scDataviz-1.22.0(bioc 3.23)

singlecellimmunooncologyrnaseqgeneexpressiontranscriptionflowcytometrymassspectrometrydataimport

6.68 score 67 stars 24 scripts 349 downloads 1 mentions 13 exports 164 dependencies

Last updated from:d6ca91b716. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE220
linux-devel-x86_64OK536
source / vignettesOK432
linux-release-x86_64OK397
macos-release-arm64OK287
macos-oldrel-arm64OK293
windows-develOK346
windows-releaseOK316
windows-oldrelOK377
wasm-releaseOK185

Exports:basethemeclusKNNcontourPlotdownsampleByVarimportDatamarkerEnrichmentmarkerExpressionmarkerExpressionPerClustermetadataPlotperformUMAPplotClustersplotSignaturesprocessFCS

Dependencies:abindaskpassbase64encBHBiobaseBiocGenericsbiocmakebitopsbslibcachemcaToolscliclustercodetoolscommonmarkcorrplotcowplotcpp11crosstalkcurlcytolibdata.tableDelayedArraydeldirdigestdir.expirydotCall64dplyrdqrngevaluatefarverfastDummiesfastmapfilelockfitdistrplusflowCoreFNNfontawesomefsfuturefuture.applygenericsGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeminiUInlmeopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulateRhdf5librlangrmarkdownROCRrprojrootRProtoBufLibRSpectraRtsneS4ArraysS4VectorsS7sassscalesscattermoresctransformSeqinfoSeuratSeuratObjectshinySingleCellExperimentsitmosourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexumaputf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzoo

scDataviz: single cell dataviz and downstream analyses

Kevin Blighe

Rendered fromscDataviz.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2021-08-07
Started: 2020-02-15

Readme and manuals

Help Manual

Help pageTopics
Package-wide, non-user function used to set a base 'ggplot2' theme.basetheme
A wrapper function for 'Seurat''s 'FindNeighbors' and 'FindClusters'.clusKNN
Draw a contour plot, typically relating to co-ordinates of a 2-dimensional reduction / embedding, typically contained within a 'SingleCellExperiment' object.contourPlot
Downsample an input data-frame or matrix based on variance.downsampleByVar
Import a data-frame or matrix, and associated metadata, to a 'SingleCellExperiment' object.importData
Find enriched markers per identified cluster and calculate cluster abundances across these for samples and metadata variables.markerEnrichment
Highlight the individual marker expression profile across a 2-dimensional reduction / embedding, typically contained within a 'SingleCellExperiment' object. By default, this function plots the expression profile of 6 randomly-selected markers from your data.markerExpression
Generate box-and-whisker plots illustrating marker expression per k-NN identified cluster. By default, 5 randomly-selected clusters are selected, and the expression profiles of 10 randomly-selected markers are plot across these.markerExpressionPerCluster
Colour shade a 2-dimensional reduction / embedding based on metadata, typically contained within a 'SingleCellExperiment' object.metadataPlot
Perform UMAP on an input data-frame or matrix, or 'SingleCellExperiment' object, using the basic R implementation of UMAP.performUMAP
Highlight cell-to-cluster assignments across a 2-dimensional reduction / embedding.plotClusters
Find enriched markers per identified cluster and visualise these as a custom corrplot.plotSignatures
Input, filter, normalise, and transform FCS expression data.processFCS