Package Recipe 'bioconductor-dittoseq'

recipe bioconductor-dittoseq

User Friendly Single-Cell and Bulk RNA Sequencing Visualization

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/dittoSeq.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-dittoseq/meta.yaml

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().

package bioconductor-dittoseq¶

Versions:

1.22.0-0, 1.18.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-0, 1.6.0-0, 1.4.1-0, 1.2.5-0, 1.2.0-0,

1.22.0-0, 1.18.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-0, 1.6.0-0, 1.4.1-0, 1.2.5-0, 1.2.0-0, 1.0.1-0

Depends:

on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-colorspace >=1.4
on r-cowplot
on r-ggplot2
on r-ggrepel
on r-ggridges
on r-gridextra
on r-pheatmap
on r-reshape2

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-dittoseq

to add into an existing workspace instead, run:

pixi add bioconductor-dittoseq

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-dittoseq

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-dittoseq

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-dittoseq:<tag>

(see bioconductor-dittoseq/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-dittoseq/README.html)