recipe bioconductor-ccfindr

A collection of tools for cancer genomic data clustering analyses, including those for single cell RNA-seq. Cell clustering and feature gene selection analysis employ Bayesian (and maximum likelihood) non-negative matrix factorization (NMF) algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks and marginal likelihood values for each rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for clusters.



GPL (>= 2)



package bioconductor-ccfindr

(downloads) docker_bioconductor-ccfindr



Depends bioconductor-s4vectors


Depends bioconductor-singlecellexperiment


Depends bioconductor-summarizedexperiment


Depends gsl


Depends libgcc-ng


Depends libstdcxx-ng


Depends openblas


Depends r-ape

Depends r-base


Depends r-gtools

Depends r-irlba

Depends r-matrix

Depends r-rcolorbrewer

Depends r-rcpp

Depends r-rcppeigen

Depends r-rmpi

Depends r-rtsne



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

conda install bioconductor-ccfindr

and update with:

conda update bioconductor-ccfindr

or use the docker container:

docker pull<tag>

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