recipe bioconductor-scddboost

A compositional model to assess expression changes from single-cell rna-seq data



GPL (>= 2)



scDDboost is an R package to analyze changes in the distribution of single-cell expression data between two experimental conditions. Compared to other methods that assess differential expression, scDDboost benefits uniquely from information conveyed by the clustering of cells into cellular subtypes. Through a novel empirical Bayesian formulation it calculates gene-specific posterior probabilities that the marginal expression distribution is the same (or different) between the two conditions. The implementation in scDDboost treats gene-level expression data within each condition as a mixture of negative binomial distributions.

package bioconductor-scddboost

(downloads) docker_bioconductor-scddboost



Required By:


With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-scddboost

and update with:

conda update bioconductor-scddboost

or use the docker container:

docker pull<tag>

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

Download stats