recipe bioconductor-ccfindr

Cancer Clone Finder

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/ccfindR.html

License:

GPL (>= 2)

Recipe:

/bioconductor-ccfindr/meta.yaml

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.

package bioconductor-ccfindr

versions:

1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.14.0-2,  1.14.0-1,  1.14.0-0,  1.12.0-0,  1.10.0-1, 

1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.14.0-2,  1.14.0-1,  1.14.0-0,  1.12.0-0,  1.10.0-1,  1.10.0-0,  1.8.0-0,  1.6.0-0,  1.4.2-0,  1.2.0-0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-s4vectors:

>=0.40.2,<0.41.0a0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0a0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0a0

depends gsl:

>=2.7,<2.8.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx-ng:

>=12

depends r-ape:

depends r-base:

>=4.3,<4.4.0a0

depends r-gtools:

depends r-irlba:

depends r-matrix:

depends r-rcolorbrewer:

depends r-rcpp:

depends r-rcppeigen:

depends r-rdpack:

>=0.7

depends r-rmpi:

depends r-rtsne:

requirements:

additional platforms:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-ccfindr

and update with::

   mamba update bioconductor-ccfindr

To create a new environment, run:

mamba create --name myenvname bioconductor-ccfindr

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

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

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