recipe bioconductor-scdd

This package implements a method to analyze single-cell RNA- seq Data utilizing flexible Dirichlet Process mixture models. Genes with differential distributions of expression are classified into several interesting patterns of differences between two conditions. The package also includes functions for simulating data with these patterns from negative binomial distributions.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/scDD.html

License

GPL-2

Recipe

/bioconductor-scdd/meta.yaml

package bioconductor-scdd

(downloads) docker_bioconductor-scdd

Versions

1.6.0-0

Depends bioconductor-biocparallel

>=1.16.0,<1.17.0

Depends bioconductor-ebseq

>=1.22.0,<1.23.0

Depends bioconductor-s4vectors

>=0.20.0,<0.21.0

Depends bioconductor-scran

>=1.10.0,<1.11.0

Depends bioconductor-singlecellexperiment

>=1.4.0,<1.5.0

Depends bioconductor-summarizedexperiment

>=1.12.0,<1.13.0

Depends r-arm

Depends r-base

>=3.5.1,<3.5.2.0a0

Depends r-fields

Depends r-ggplot2

Depends r-mclust

Depends r-outliers

Requirements

Installation

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

conda install bioconductor-scdd

and update with:

conda update bioconductor-scdd

or use the docker container:

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

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