Package Recipe 'bioconductor-cardspa'

recipe bioconductor-cardspa

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.

package bioconductor-cardspa¶

Versions:

1.2.1-0

Depends:

on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-biocparallel >=1.44.0,<1.45.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0a0
on bioconductor-spatialexperiment >=1.20.0,<1.21.0
on bioconductor-spatialexperiment >=1.20.0,<1.21.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-concaveman
on r-dplyr
on r-fields
on r-ggcorrplot
on r-ggplot2
on r-gtools
on r-matrix
on r-mcmcpack
on r-nmf
on r-nnls
on r-rann
on r-rcolorbrewer
on r-rcpp >=1.0.7
on r-rcpparmadillo
on r-reshape2
on r-scatterpie
on r-sf
on r-sp
on r-spatstat.random
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 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-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 Usage), 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:<tag>

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