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.

Homepage

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

License

GPL (>= 2)

Recipe

/bioconductor-ccfindr/meta.yaml

package bioconductor-ccfindr

Versions

1.2.0-0

Depends

• bioconductor-s4vectors >=0.20.0,<0.21.0

• bioconductor-singlecellexperiment >=1.4.0,<1.5.0

• bioconductor-summarizedexperiment >=1.12.0,<1.13.0

• gsl >=2.4,<2.5.0a0

• libgcc-ng >=7.3.0

• libstdcxx-ng >=7.3.0

• openblas >=0.3.3,<0.3.4.0a0

• r-ape

• r-base >=3.5.1,<3.5.2.0a0

• r-gtools

• r-irlba

• r-matrix

• r-rcolorbrewer

• r-rcpp

• r-rcppeigen

• r-rmpi

• r-rtsne

Required By

Installation

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 quay.io/biocontainers/bioconductor-ccfindr:<tag>

(see bioconductor-ccfindr/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-ccfindr/README.html)