recipe bioconductor-dittoseq

User Friendly Single-Cell and Bulk RNA Sequencing Visualization

Homepage:

https://bioconductor.org/packages/3.18/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:

1.14.0-0,  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 bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-colorspace:

>=1.4

depends r-cowplot:

depends r-ggplot2:

depends r-ggrepel:

depends r-ggridges:

depends r-gridextra:

depends r-pheatmap:

depends r-reshape2:

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-dittoseq

and update with::

   mamba update bioconductor-dittoseq

To create a new environment, run:

mamba create --name myenvname bioconductor-dittoseq

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

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

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)