- recipe bioconductor-diffcyt
Differential discovery in high-dimensional cytometry via high-resolution clustering
- Homepage
https://bioconductor.org/packages/3.14/bioc/html/diffcyt.html
- License
MIT + file LICENSE
- Recipe
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
1.14.0-0
,1.12.0-0
,1.10.0-1
,1.10.0-0
,1.8.6-0
,1.6.0-0
,1.4.3-0
,1.2.23-1
,1.2.0-0
- Depends
bioconductor-complexheatmap
>=2.10.0,<2.11.0
bioconductor-edger
>=3.36.0,<3.37.0
bioconductor-flowcore
>=2.6.0,<2.7.0
bioconductor-flowsom
>=2.2.0,<2.3.0
bioconductor-limma
>=3.50.0,<3.51.0
bioconductor-s4vectors
>=0.32.0,<0.33.0
bioconductor-summarizedexperiment
>=1.24.0,<1.25.0
r-base
>=4.1,<4.2.0a0
- 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>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-diffcyt/README.html)