recipe bioconductor-scrnaseqapp

A single-cell RNAseq Shiny app-package

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/scRNAseqApp.html

License:

GPL-3

Recipe:

/bioconductor-scrnaseqapp/meta.yaml

The scRNAseqApp is a Shiny app package designed for interactive visualization of single-cell data. It is an enhanced version derived from the ShinyCell, repackaged to accommodate multiple datasets. The app enables users to visualize data containing various types of information simultaneously, facilitating comprehensive analysis. Additionally, it includes a user management system to regulate database accessibility for different users.

package bioconductor-scrnaseqapp

versions:

1.6.0-0,  1.2.2-0,  1.0.1-0

depends bioconductor-complexheatmap:

>=2.22.0,<2.23.0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-iranges:

>=2.40.0,<2.41.0

depends bioconductor-rhdf5:

>=2.50.0,<2.51.0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0

depends bioconductor-rtracklayer:

>=1.66.0,<1.67.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-singlecellexperiment:

>=1.28.0,<1.29.0

depends bioconductor-slingshot:

>=2.14.0,<2.15.0

depends r-base:

>=4.4,<4.5.0a0

depends r-bibtex:

depends r-bslib:

depends r-circlize:

depends r-colourpicker:

depends r-data.table:

depends r-dbi:

depends r-dt:

depends r-ggdendro:

depends r-ggforce:

depends r-ggplot2:

depends r-ggrepel:

depends r-ggridges:

depends r-gridextra:

depends r-htmltools:

depends r-jsonlite:

depends r-magrittr:

depends r-patchwork:

depends r-plotly:

depends r-rcolorbrewer:

depends r-refmanager:

depends r-rsqlite:

depends r-scales:

depends r-scrypt:

depends r-seurat:

depends r-seuratobject:

depends r-shiny:

depends r-shinyhelper:

depends r-shinymanager:

depends r-sortable:

depends r-xfun:

depends r-xml2:

requirements:

additional platforms:

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-scrnaseqapp

and update with::

   mamba update bioconductor-scrnaseqapp

To create a new environment, run:

mamba create --name myenvname bioconductor-scrnaseqapp

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-scrnaseqapp:<tag>

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

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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-scrnaseqapp/README.html)