:orphan: .. only available via index, not via toctree .. title:: Package Recipe 'bioconductor-cardspa' .. highlight: bash bioconductor-cardspa ==================== .. conda:recipe:: bioconductor-cardspa :replaces_section_title: :noindex: Spatially Informed Cell Type Deconvolution for Spatial Transcriptomics :homepage: https://bioconductor.org/packages/3.22/bioc/html/CARDspa.html :license: GPL-3 + file LICENSE :recipe: /`bioconductor-cardspa `_/`meta.yaml `_ CARD is a reference\-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA\-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations\, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes. .. conda:package:: bioconductor-cardspa |downloads_bioconductor-cardspa| |docker_bioconductor-cardspa| :versions: ``1.2.1-0`` :depends on bioconductor-biocparallel: ``>=1.44.0,<1.45.0`` :depends on bioconductor-biocparallel: ``>=1.44.0,<1.45.0a0`` :depends on bioconductor-s4vectors: ``>=0.48.0,<0.49.0`` :depends on bioconductor-s4vectors: ``>=0.48.0,<0.49.0a0`` :depends on bioconductor-singlecellexperiment: ``>=1.32.0,<1.33.0`` :depends on bioconductor-singlecellexperiment: ``>=1.32.0,<1.33.0a0`` :depends on bioconductor-spatialexperiment: ``>=1.20.0,<1.21.0`` :depends on bioconductor-spatialexperiment: ``>=1.20.0,<1.21.0a0`` :depends on bioconductor-summarizedexperiment: ``>=1.40.0,<1.41.0`` :depends on bioconductor-summarizedexperiment: ``>=1.40.0,<1.41.0a0`` :depends on libblas: ``>=3.9.0,<4.0a0`` :depends on libgcc: ``>=14`` :depends on liblapack: ``>=3.9.0,<4.0a0`` :depends on liblzma: ``>=5.8.2,<6.0a0`` :depends on libstdcxx: ``>=14`` :depends on libzlib: ``>=1.3.1,<2.0a0`` :depends on r-base: ``>=4.5,<4.6.0a0`` :depends on r-concaveman: :depends on r-dplyr: :depends on r-fields: :depends on r-ggcorrplot: :depends on r-ggplot2: :depends on r-gtools: :depends on r-matrix: :depends on r-mcmcpack: :depends on r-nmf: :depends on r-nnls: :depends on r-rann: :depends on r-rcolorbrewer: :depends on r-rcpp: ``>=1.0.7`` :depends on r-rcpparmadillo: :depends on r-reshape2: :depends on r-scatterpie: :depends on r-sf: :depends on r-sp: :depends on r-spatstat.random: :depends on r-wrmisc: :additional platforms: Installation ------------ You need a conda-compatible package manager (currently either `pixi `__, `conda `__, or `micromamba `__) and the Bioconda channel already activated (see :ref:`bioconda_setup`). 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 :ref:`bioconda_setup`), to install globally, run:: pixi global install bioconductor-cardspa to add into an existing workspace instead, run:: pixi add bioconductor-cardspa 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 :ref:`bioconda_setup`), to install into an existing and activated environment, run:: conda install bioconductor-cardspa Alternatively, to install into a new environment, run:: conda create -n envname bioconductor-cardspa 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-cardspa: (see `bioconductor-cardspa/tags`_ for valid values for ````). 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. .. _conda: https://conda.io .. _pixi: https://pixi.sh .. |downloads_bioconductor-cardspa| image:: https://img.shields.io/conda/dn/bioconda/bioconductor-cardspa.svg?style=flat :target: https://anaconda.org/bioconda/bioconductor-cardspa :alt: (downloads) .. |docker_bioconductor-cardspa| image:: https://quay.io/repository/biocontainers/bioconductor-cardspa/status :target: https://quay.io/repository/biocontainers/bioconductor-cardspa .. _`bioconductor-cardspa/tags`: https://quay.io/repository/biocontainers/bioconductor-cardspa?tab=tags .. raw:: html Download stats ----------------- .. raw:: html :file: ../../templates/package_dashboard.html Link to this page ----------------- Render an |install-with-bioconda| 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-cardspa/README.html) .. |install-with-bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/bioconductor-cardspa/README.html