recipe bioconductor-fci

f-divergence Cutoff Index for Differential Expression Analysis in Transcriptomics and Proteomics

Homepage:

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

License:

GPL (>= 2)

Recipe:

/bioconductor-fci/meta.yaml

(f-divergence Cutoff Index), is to find DEGs in the transcriptomic & proteomic data, and identify DEGs by computing the difference between the distribution of fold-changes for the control-control and remaining (non-differential) case-control gene expression ratio data. fCI provides several advantages compared to existing methods.

package bioconductor-fci

(downloads) docker_bioconductor-fci

versions:
1.32.0-01.30.0-01.28.0-01.24.0-01.22.0-01.20.0-11.20.0-01.18.0-01.16.0-0

1.32.0-01.30.0-01.28.0-01.24.0-01.22.0-01.20.0-11.20.0-01.18.0-01.16.0-01.14.0-11.14.0-01.12.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-fnn:

depends r-gtools:

depends r-psych:

depends r-rgl:

depends r-venndiagram:

depends r-zoo:

requirements:

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-fci

and update with::

   mamba update bioconductor-fci

To create a new environment, run:

mamba create --name myenvname bioconductor-fci

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-fci:<tag>

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

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