recipe bioconductor-diffcyt

Differential discovery in high-dimensional cytometry via high-resolution clustering

Homepage

https://bioconductor.org/packages/3.11/bioc/html/diffcyt.html

License

MIT + file LICENSE

Recipe

/bioconductor-diffcyt/meta.yaml

Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.

package bioconductor-diffcyt

Versions

1.8.6-0,  1.6.0-0,  1.4.3-0,  1.2.23-1,  1.2.0-0

Depends

• bioconductor-complexheatmap >=2.4.0,<2.5.0

• bioconductor-edger >=3.30.0,<3.31.0

• bioconductor-flowcore >=2.0.0,<2.1.0

• bioconductor-flowsom >=1.20.0,<1.21.0

• bioconductor-limma >=3.44.0,<3.45.0

• bioconductor-s4vectors >=0.26.0,<0.27.0

• bioconductor-summarizedexperiment >=1.18.0,<1.19.0

• r-base >=4.0,<4.1.0a0

• r-circlize

• r-dplyr

• r-lme4

• r-magrittr

• r-multcomp

• r-reshape2

• r-tidyr

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-diffcyt

and update with:

conda update bioconductor-diffcyt

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-diffcyt:<tag>

(see bioconductor-diffcyt/tags for valid values for <tag>)

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-diffcyt/README.html)