Package Recipe 'bioconductor-ccfindr'

recipe bioconductor-ccfindr

Cancer Clone Finder

Homepage:: https://bioconductor.org/packages/3.20/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:

1.30.0-0, 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,

1.30.0-0, 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:

on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-ape
on r-base >=4.5,<4.6.0a0
on r-gtools
on r-irlba
on r-matrix
on r-rcolorbrewer
on r-rcpp
on r-rcppeigen
on r-rdpack >=0.7
on r-rmpi
on r-rtsne

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-ccfindr

to add into an existing workspace instead, run:

pixi add bioconductor-ccfindr

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-ccfindr

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-ccfindr

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

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)