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User Friendly Single-Cell and Bulk RNA Sequencing Visualization

Bioconductor version: Release (3.19)

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().

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

Maintainer: Daniel Bunis <daniel.bunis at>

Citation (from within R, enter citation("dittoSeq")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Annotating scRNA-seq data HTML R Script
Reference Manual PDF


biocViews DataImport, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics, Visualization
Version 1.16.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License MIT + file LICENSE
Depends ggplot2
Imports methods, colorspace (>= 1.4), gridExtra, cowplot, reshape2, pheatmap, grDevices, ggrepel, ggridges, stats, utils, SummarizedExperiment, SingleCellExperiment, S4Vectors
System Requirements
See More
Suggests plotly, testthat, Seurat (>= 2.2), DESeq2, edgeR, ggplot.multistats, knitr, rmarkdown, BiocStyle, scRNAseq, ggrastr (>= 0.2.0), ComplexHeatmap, bluster, scater, scran
Linking To
Depends On Me
Imports Me CRISPRball, SPIAT
Suggests Me demuxSNP, tidySingleCellExperiment, tidySpatialExperiment, magmaR, scCustomize
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package dittoSeq_1.16.0.tar.gz
Windows Binary
macOS Binary (x86_64) dittoSeq_1.16.0.tgz
macOS Binary (arm64) dittoSeq_1.16.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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