recipe bioconductor-simpleseg

A package to perform simple cell segmentation

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-simpleseg/meta.yaml

Image segmentation is the process of identifying the borders of individual objects (in this case cells) within an image. This allows for the features of cells such as marker expression and morphology to be extracted, stored and analysed. simpleSeg provides functionality for user friendly, watershed based segmentation on multiplexed cellular images in R based on the intensity of user specified protein marker channels. simpleSeg can also be used for the normalization of single cell data obtained from multiple images.

package bioconductor-simpleseg

(downloads) docker_bioconductor-simpleseg

Versions:

1.12.0-0,  1.8.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-0

Depends:

  • on bioconductor-biocparallel >=1.44.0,<1.45.0

  • on bioconductor-cytomapper >=1.22.0,<1.23.0

  • on bioconductor-ebimage >=4.52.0,<4.53.0

  • on bioconductor-s4vectors >=0.48.0,<0.49.0

  • on bioconductor-summarizedexperiment >=1.40.0,<1.41.0

  • on r-base >=4.5,<4.6.0a0

  • on r-spatstat.geom

  • on r-terra

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-simpleseg

to add into an existing workspace instead, run:

pixi add bioconductor-simpleseg

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-simpleseg

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-simpleseg

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-simpleseg:<tag>

(see bioconductor-simpleseg/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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Render an install-with-bioconda badge with the following MarkDown:

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