recipe bioconductor-famat

Functional analysis of metabolic and transcriptomic data

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-famat/meta.yaml

Famat is made to collect data about lists of genes and metabolites provided by user, and to visualize it through a Shiny app. Information collected is: - Pathways containing some of the user's genes and metabolites (obtained using a pathway enrichment analysis). - Direct interactions between user's elements inside pathways. - Information about elements (their identifiers and descriptions). - Go terms enrichment analysis performed on user's genes. The Shiny app is composed of: - information about genes, metabolites, and direct interactions between them inside pathways. - an heatmap showing which elements from the list are in pathways (pathways are structured in hierarchies). - hierarchies of enriched go terms using Molecular Function and Biological Process.

package bioconductor-famat

versions:

1.12.0-0,  1.10.0-0,  1.8.0-0,  1.4.0-0,  1.1.1-0,  1.0.0-1,  1.0.0-0

depends bioconductor-clusterprofiler:

>=4.10.0,<4.11.0

depends bioconductor-go.db:

>=3.18.0,<3.19.0

depends bioconductor-keggrest:

>=1.42.0,<1.43.0

depends bioconductor-org.hs.eg.db:

>=3.18.0,<3.19.0

depends bioconductor-reactome.db:

>=1.86.0,<1.87.0

depends bioconductor-rwikipathways:

>=1.22.0,<1.23.0

depends r-base:

>=4.3,<4.4.0a0

depends r-biasedurn:

depends r-dplyr:

depends r-dt:

depends r-gprofiler2:

depends r-magrittr:

depends r-mgcv:

depends r-ontologyindex:

depends r-plotly:

depends r-shiny:

depends r-shinybs:

depends r-shinydashboard:

depends r-stringr:

depends r-tidyr:

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-famat

and update with::

   mamba update bioconductor-famat

To create a new environment, run:

mamba create --name myenvname bioconductor-famat

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-famat:<tag>

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

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