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✨
DESCRIPTION |NEWS
card.svg |card.png
scDataviz/json (API)

# 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)

singlecell immunooncology rnaseq geneexpression transcription flowcytometry massspectrometry dataimport

6.58 score 67 stars 19 scripts 1 mentions 13 exports 164 dependencies

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

Target	Result	Time
bioc-checks	NOTE	223
linux-devel-x86_64	OK	434
source / vignettes	OK	471
linux-release-x86_64	OK	399
macos-release-arm64	OK	225
macos-oldrel-arm64	OK	247
windows-devel	OK	307
windows-release	OK	316
windows-oldrel	OK	346
wasm-release	OK	220

Exports:basetheme clusKNN contourPlot downsampleByVar importData markerEnrichment markerExpression markerExpressionPerCluster metadataPlot performUMAP plotClusters plotSignatures processFCS

Dependencies:abind askpass base64enc BH Biobase BiocGenerics biocmake bitops bslib cachem caTools cli cluster codetools commonmark corrplot cowplot cpp11 crosstalk curl cytolib data.table DelayedArray deldir digest dir.expiry dotCall64 dplyr dqrng evaluate farver fastDummies fastmap filelock fitdistrplus flowCore FNN fontawesome fs future future.apply generics GenomicRanges ggplot2 ggrepel ggridges globals glue goftest gplots gridExtra gtable gtools here highr htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval lifecycle listenv lmtest magrittr MASS Matrix MatrixGenerics matrixStats memoise mime miniUI nlme openssl otel parallelly patchwork pbapply pillar pkgconfig plotly plyr png polyclip progressr promises purrr R6 RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppProgress RcppTOML reshape2 reticulate Rhdf5lib rlang rmarkdown ROCR rprojroot RProtoBufLib RSpectra Rtsne S4Arrays S4Vectors S7 sass scales scattermore sctransform Seqinfo Seurat SeuratObject shiny SingleCellExperiment sitmo sourcetools sp spam SparseArray spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils stringi stringr SummarizedExperiment survival sys tensor tibble tidyr tidyselect tinytex umap utf8 uwot vctrs viridisLite withr xfun xtable XVector yaml zoo

scDataviz: single cell dataviz and downstream analyses

Rendered fromscDataviz.Rmdusingknitr::rmarkdown

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

Help page	Topics
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

Package: scDataviz 1.23.0

scDataviz: scDataviz: single cell dataviz and downstream analyses

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