Package: dittoSeq 1.17.0

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_1.17.0.tar.gz
dittoSeq_1.17.0.zip(r-4.5)dittoSeq_1.17.0.zip(r-4.4)dittoSeq_1.17.0.zip(r-4.3)
dittoSeq_1.17.0.tgz(r-4.4-any)dittoSeq_1.17.0.tgz(r-4.3-any)
dittoSeq_1.17.0.tar.gz(r-4.5-noble)dittoSeq_1.17.0.tar.gz(r-4.4-noble)
dittoSeq_1.17.0.tgz(r-4.4-emscripten)dittoSeq_1.17.0.tgz(r-4.3-emscripten)
dittoSeq.pdf |dittoSeq.html✨
dittoSeq/json (API)
NEWS

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

Peer review:

Datasets:

On BioConductor:dittoSeq-1.17.0(bioc 3.20)dittoSeq-1.16.0(bioc 3.19)

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

bioconductor-package

36 exports 2.05 score 64 dependencies 2 dependents

Last updated 2 months agofrom:3f77dfe453

Exports:addDimReductionaddPrcompDarkendemux.calls.summarydemux.SNP.summarydittoBarPlotdittoBoxPlotdittoColorsdittoDimHexdittoDimPlotdittoDotPlotdittoFreqPlotdittoHeatmapdittoPlotdittoPlotVarsAcrossGroupsdittoRidgeJitterdittoRidgePlotdittoScatterHexdittoScatterPlotgenegetGenesgetMetasgetReductionsimportDemuximportDittoBulkisBulkisGeneisMetaLightenmetametaLevelsmulti_dittoDimPlotmulti_dittoDimPlotVaryCellsmulti_dittoPlotsetBulkSimulate

Dependencies:abindaskpassBiobaseBiocGenericsclicolorspacecowplotcrayoncurlDelayedArrayfansifarverGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesgluegridExtragtablehttrIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpheatmappillarpkgconfigplyrR6RColorBrewerRcppreshape2rlangS4ArraysS4VectorsscalesSingleCellExperimentSparseArraystringistringrSummarizedExperimentsystibbleUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc

Using dittoSeq to visualize (sc)RNAseq data

Daniel Bunis

Rendered fromdittoSeq.Rmdusingknitr::rmarkdownon Jun 30 2024.

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

Readme and manuals

Help Manual

Help pageTopics
Add any dimensionality reduction space to a SingleCellExperiment object containing bulk or single-cell dataaddDimReduction
Add a prcomp pca calculation to a SingleCellExperiment object containing bulk or single-cell dataaddPrcomp
Darkens input colors by a set amountDarken
Plots the number of annotations per sample, per lanedemux.calls.summary
Plots the number of SNPs sequenced per dropletdemux.SNP.summary
demuxlet.exampledemuxlet.example
Outputs a stacked bar plot to show the percent composition of samples, groups, clusters, or other groupingsdittoBarPlot
Extracts the dittoSeq default colorsdittoColors
Shows data overlayed on a tsne, pca, or similar type of plotdittoDimPlot
Compact plotting of per group summaries for expression of multiple featuresdittoDotPlot
Plot cell type/cluster/identity frequencies per sample and per groupingdittoFreqPlot
Outputs a heatmap of given genesdittoHeatmap
Show RNAseq data, grouped into hexagonal bins, on a scatter or dimensionality reduction plotdittoDimHex dittoHex dittoScatterHex
Plots continuous data for customizeable cells'/samples' groupings on a y- (or x-) axisdittoBoxPlot 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 plotdittoScatterPlot
dittoSeqdittoSeq-package dittoSeq
Returns the expression values of a gene for all cells/samplesgene
Control of Gene/Feature targetingGeneTargeting
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 objectimportDemux
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 dittoSeqisBulk
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 amountLighten
Returns the values of a meta.data for all cells/samplesmeta
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 cellsmulti_dittoDimPlotVaryCells
Generates dittoPlots for multiple features.multi_dittoPlot
Set whether a SingleCellExperiment object should be treated as bulk versus single-cell by dittoSeqsetBulk setBulk,SingleCellExperiment-method
Simulates what a colorblind person would see for any dittoSeq plot!Simulate