Package: dittoSeq 1.25.0

Daniel Bunis

dittoSeq: User Friendly Single-Cell and Bulk RNA Sequencing Visualization

A universal, user friendly, single-cell and bulk RNA sequencing visualization toolkit that allows highly customizable creation of color blindness friendly, publication-quality figures. dittoSeq accepts both SingleCellExperiment (SCE) and Seurat objects, as well as the import and usage, via conversion to an SCE, of SummarizedExperiment or DGEList bulk data. Visualizations include dimensionality reduction plots, heatmaps, scatterplots, percent composition or expression across groups, and more. Customizations range from size and title adjustments to automatic generation of annotations for heatmaps, overlay of trajectory analysis onto any dimensionality reduciton plot, hidden data overlay upon cursor hovering via ggplotly conversion, and many more. All with simple, discrete inputs. Color blindness friendliness is powered by legend adjustments (enlarged keys), and by allowing the use of shapes or letter-overlay in addition to the carefully selected dittoColors().

Authors:Daniel Bunis [aut, cre], Jared Andrews [aut, ctb]

dittoSeq_1.25.0.tar.gz
dittoSeq_1.25.0.zip(r-4.7)dittoSeq_1.25.0.zip(r-4.6)dittoSeq_1.25.0.zip(r-4.5)
dittoSeq_1.25.0.tgz(r-4.6-any)dittoSeq_1.25.0.tgz(r-4.5-any)
dittoSeq_1.25.0.tar.gz(r-4.7-any)dittoSeq_1.25.0.tar.gz(r-4.6-any)
dittoSeq_1.25.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dittoSeq/json (API)

# Install 'dittoSeq' in R:

install.packages('dittoSeq', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

demuxlet.example - Demuxlet.example

On BioConductor:dittoSeq-1.25.0(bioc 3.24)dittoSeq-1.24.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

software visualization rnaseq singlecell geneexpression transcriptomics dataimport

7.36 score 2 packages 1.9k scripts 36 exports 47 dependencies

Last updated from:ae7346c1c4. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	288
linux-devel-x86_64	NOTE	537
source / vignettes	OK	430
linux-release-x86_64	NOTE	614
macos-release-arm64	NOTE	313
macos-oldrel-arm64	NOTE	268
windows-devel	NOTE	1640
windows-release	NOTE	1688
windows-oldrel	NOTE	1647
wasm-release	OK	254

Exports:addDimReduction addPrcomp Darken demux.calls.summary demux.SNP.summary dittoBarPlot dittoBoxPlot dittoColors dittoDimHex dittoDimPlot dittoDotPlot dittoFreqPlot dittoHeatmap dittoPlot dittoPlotVarsAcrossGroups dittoRidgeJitter dittoRidgePlot dittoScatterHex dittoScatterPlot gene getGenes getMetas getReductions importDemux importDittoBulk isBulk isGene isMeta Lighten meta metaLevels multi_dittoDimPlot multi_dittoDimPlotVaryCells multi_dittoPlot setBulk Simulate

Dependencies:abind Biobase BiocGenerics cli colorspace cowplot cpp11 DelayedArray farver generics GenomicRanges ggplot2 ggrepel ggridges glue gridExtra gtable IRanges isoband labeling lattice lifecycle magrittr Matrix MatrixGenerics matrixStats pheatmap plyr R6 RColorBrewer Rcpp reshape2 rlang S4Arrays S4Vectors S7 scales Seqinfo SingleCellExperiment SparseArray stringi stringr SummarizedExperiment vctrs viridisLite withr XVector

Using dittoSeq to visualize (sc)RNAseq data

Rendered fromdittoSeq.Rmdusingknitr::rmarkdown

Last update: 2021-05-27
Started: 2019-11-10

Help page	Topics
Add any dimensionality reduction space to a SingleCellExperiment object containing bulk or single-cell data	addDimReduction
Add a prcomp pca calculation to a SingleCellExperiment object containing bulk or single-cell data	addPrcomp
Darkens input colors by a set amount	Darken
Plots the number of annotations per sample, per lane	demux.calls.summary
Plots the number of SNPs sequenced per droplet	demux.SNP.summary
demuxlet.example	demuxlet.example
Outputs a stacked bar plot to show the percent composition of samples, groups, clusters, or other groupings	dittoBarPlot
Extracts the dittoSeq default colors	dittoColors
Shows data overlayed on a tsne, pca, or similar type of plot	dittoDimPlot
Compact plotting of per group summaries for expression of multiple features	dittoDotPlot
Plot cell type/cluster/identity frequencies per sample and per grouping	dittoFreqPlot
Outputs a heatmap of given genes	dittoHeatmap
Show RNAseq data, grouped into hexagonal bins, on a scatter or dimensionality reduction plot	dittoDimHex dittoHex dittoScatterHex
Plots continuous data for customizeable cells'/samples' groupings on a y- (or x-) axis	dittoBoxPlot dittoPlot dittoRidgeJitter dittoRidgePlot
Generates a dittoPlot where data points are genes/metadata summaries, per groups, instead of individual values per cells/samples.	dittoPlotVarsAcrossGroups
Show RNAseq data overlayed on a scatter plot	dittoScatterPlot
dittoSeq	dittoSeq-package dittoSeq
Returns the expression values of a gene for all cells/samples	gene
Control of Gene/Feature targeting	GeneTargeting
Returns the names of all genes of a target object.	getGenes
Returns the names of all meta.data slots of a target object.	getMetas
Returns the names of all dimensionality reduction slots of a target object.	getReductions
Extracts Demuxlet information into a pre-made SingleCellExperiment or Seurat object	importDemux
import bulk sequencing data into a SingleCellExperiment format that will work with other dittoSeq functions.	importDittoBulk
Retrieve whether a given object would be treated as bulk versus single-cell by dittoSeq	isBulk
Tests if input is the name of a gene in a target object.	isGene
Tests if an input is the name of a meta.data slot in a target object.	isMeta
Lightens input colors by a set amount	Lighten
Returns the values of a meta.data for all cells/samples	meta
Gives the distinct values of a meta.data slot (or ident)	metaLevels
Generates dittoDimPlots for multiple features.	multi_dittoDimPlot
Generates multiple dittoDimPlots, for a single feature, where each showing different cells	multi_dittoDimPlotVaryCells
Generates dittoPlots for multiple features.	multi_dittoPlot
Set whether a SingleCellExperiment object should be treated as bulk versus single-cell by dittoSeq	setBulk setBulk,SingleCellExperiment-method
Simulates what a colorblind person would see for any dittoSeq plot!	Simulate

Package: dittoSeq 1.25.0

dittoSeq: User Friendly Single-Cell and Bulk RNA Sequencing Visualization

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Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)