Package Recipe 'bioconductor-spatialcpie'

recipe bioconductor-spatialcpie

Cluster analysis of Spatial Transcriptomics data

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

SpatialCPie is an R package designed to facilitate cluster evaluation for spatial transcriptomics data by providing intuitive visualizations that display the relationships between clusters in order to guide the user during cluster identification and other downstream applications. The package is built around a shiny "gadget" to allow the exploration of the data with multiple plots in parallel and an interactive UI. The user can easily toggle between different cluster resolutions in order to choose the most appropriate visual cues.

package bioconductor-spatialcpie¶

Versions:

1.26.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-0, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0,

1.26.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-0, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-1

Depends:

on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-colorspace >=1.3-2
on r-data.table >=1.12.2
on r-digest >=0.6.21
on r-dplyr >=0.7.6
on r-ggforce >=0.3.0
on r-ggiraph >=0.5.0
on r-ggplot2 >=3.0.0
on r-ggrepel >=0.8.0
on r-igraph >=1.2.2
on r-lpsolve >=5.6.13
on r-purrr >=0.2.5
on r-readr >=1.1.1
on r-rlang >=0.2.2
on r-shiny >=1.1.0
on r-shinycssloaders >=0.2.0
on r-shinyjs >=1.0
on r-shinywidgets >=0.4.8
on r-tibble >=1.4.2
on r-tidyr >=0.8.1
on r-tidyselect >=0.2.4
on r-zeallot >=0.1.0

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-spatialcpie

to add into an existing workspace instead, run:

pixi add bioconductor-spatialcpie

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-spatialcpie

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-spatialcpie

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-spatialcpie:<tag>

(see bioconductor-spatialcpie/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-spatialcpie/README.html)