Package Recipe 'bioconductor-catalyst'

recipe bioconductor-catalyst

Cytometry dATa anALYSis Tools

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/CATALYST.html
License:: GPL (>=2)
Recipe:: /bioconductor-catalyst/meta.yaml

CATALYST provides tools for preprocessing of and differential discovery in cytometry data such as FACS, CyTOF, and IMC. Preprocessing includes i) normalization using bead standards, ii) single-cell deconvolution, and iii) bead-based compensation. For differential discovery, the package provides a number of convenient functions for data processing (e.g., clustering, dimension reduction), as well as a suite of visualizations for exploratory data analysis and exploration of results from differential abundance (DA) and state (DS) analysis in order to identify differences in composition and expression profiles at the subpopulation-level, respectively.

package bioconductor-catalyst¶

Versions:

1.34.1-0, 1.30.0-0, 1.26.0-0, 1.24.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-1, 1.14.0-0,

1.34.1-0, 1.30.0-0, 1.26.0-0, 1.24.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-1, 1.14.0-0, 1.12.1-0, 1.10.0-0, 1.8.6-0, 1.6.0-0

Depends:

on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-consensusclusterplus >=1.74.0,<1.75.0
on bioconductor-flowcore >=2.22.0,<2.23.0
on bioconductor-flowsom >=2.18.0,<2.19.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-scater >=1.38.0,<1.39.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-cowplot
on r-data.table
on r-dplyr
on r-drc
on r-ggplot2
on r-ggrepel
on r-ggridges
on r-gridextra
on r-matrix
on r-matrixstats
on r-nnls
on r-purrr
on r-rcolorbrewer
on r-reshape2
on r-rtsne
on r-scales

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-catalyst

to add into an existing workspace instead, run:

pixi add bioconductor-catalyst

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-catalyst

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-catalyst

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-catalyst:<tag>

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