recipe bioconductor-spacexr

SpatialeXpressionR: Cell Type Identification in Spatial Transcriptomics

Homepage:

https://bioconductor.org/packages/3.22/bioc/html/spacexr.html

License:

GPL (>= 3)

Recipe:

/bioconductor-spacexr/meta.yaml

Spatial-eXpression-R (spacexr) is a package for analyzing cell types in spatial transcriptomics data. This implementation is a fork of the spacexr GitHub repo (https://github.com/dmcable/spacexr), adapted to work with Bioconductor objects. The original package implements two statistical methods: RCTD for learning cell types and CSIDE for inferring cell type-specific differential expression. Currently, this fork only implements RCTD, which learns cell type profiles from annotated RNA sequencing (RNA-seq) reference data and uses these profiles to identify cell types in spatial transcriptomic pixels while accounting for platform-specific effects. Future releases will include an implementation of CSIDE.

package bioconductor-spacexr

(downloads) docker_bioconductor-spacexr

Versions:

1.2.0-0

Depends:

  • on bioconductor-biocfilecache >=3.0.0,<3.1.0

  • on bioconductor-biocparallel >=1.44.0,<1.45.0

  • on bioconductor-spatialexperiment >=1.20.0,<1.21.0

  • on bioconductor-summarizedexperiment >=1.40.0,<1.41.0

  • on r-base >=4.5,<4.6.0a0

  • on r-ggplot2

  • on r-httr

  • on r-matrix

  • on r-memoise

  • on r-quadprog

  • on r-scatterpie

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-spacexr

to add into an existing workspace instead, run:

pixi add bioconductor-spacexr

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-spacexr

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-spacexr

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-spacexr:<tag>

(see bioconductor-spacexr/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.

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