:orphan:  .. only available via index, not via toctree

.. title:: Package Recipe 'bioconductor-irisfgm'
.. highlight: bash

bioconductor-irisfgm
====================

.. conda:recipe:: bioconductor-irisfgm
   :replaces_section_title:
   :noindex:

   Comprehensive Analysis of Gene Interactivity Networks Based on Single\-Cell RNA\-Seq

   :homepage: https://bioconductor.org/packages/3.17/bioc/html/IRISFGM.html
   :license: GPL-2
   :recipe: /`bioconductor-irisfgm <https://github.com/bioconda/bioconda-recipes/tree/master/recipes/bioconductor-irisfgm>`_/`meta.yaml <https://github.com/bioconda/bioconda-recipes/tree/master/recipes/bioconductor-irisfgm/meta.yaml>`_

   Single\-cell RNA\-Seq data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically\, the investigation of functional gene modules \(FGM\) can help to understand gene interactive networks and complex biological processes. QUBIC2 is recognized as one of the most efficient and effective tools for FGM identification from scRNA\-Seq data. However\, its availability is limited to a C implementation\, and its applicative power is affected by only a few downstream analyses functionalities. We developed an R package named IRIS\-FGM \(integrative scRNA\-Seq interpretation system for functional gene module analysis\) to support the investigation of FGMs and cell clustering using scRNA\-Seq data. Empowered by QUBIC2\, IRIS\-FGM can identify co\-expressed and co\-regulated FGMs\, predict types\/clusters\, identify differentially expressed genes\, and perform functional enrichment analysis. It is noteworthy that IRIS\-FGM also applies Seurat objects that can be easily used in the Seurat vignettes.


.. conda:package:: bioconductor-irisfgm

   |downloads_bioconductor-irisfgm| |docker_bioconductor-irisfgm|

   :versions:
      
      

      ``1.8.0-0``,  ``1.6.0-0``,  ``1.2.0-2``,  ``1.2.0-1``,  ``1.2.0-0``,  ``1.0.0-0``

      

   
   :depends bioconductor-annotationdbi: ``>=1.62.0,<1.63.0``
   :depends bioconductor-clusterprofiler: ``>=4.8.0,<4.9.0``
   :depends bioconductor-desingle: ``>=1.20.0,<1.21.0``
   :depends bioconductor-org.hs.eg.db: ``>=3.17.0,<3.18.0``
   :depends bioconductor-org.mm.eg.db: ``>=3.17.0,<3.18.0``
   :depends bioconductor-scater: ``>=1.28.0,<1.29.0``
   :depends bioconductor-scran: ``>=1.28.0,<1.29.0``
   :depends bioconductor-singlecellexperiment: ``>=1.22.0,<1.23.0``
   :depends libblas: ``>=3.9.0,<4.0a0``
   :depends libgcc-ng: ``>=12``
   :depends liblapack: ``>=3.9.0,<4.0a0``
   :depends libstdcxx-ng: ``>=12``
   :depends r-adaptgauss: 
   :depends r-anocva: 
   :depends r-base: ``>=4.3,<4.4.0a0``
   :depends r-colorspace: 
   :depends r-drimpute: 
   :depends r-ggplot2: 
   :depends r-ggpubr: 
   :depends r-ggraph: 
   :depends r-igraph: 
   :depends r-knitr: 
   :depends r-matrix: 
   :depends r-mcl: 
   :depends r-mixtools: 
   :depends r-pheatmap: 
   :depends r-polychrome: 
   :depends r-rcolorbrewer: 
   :depends r-rcpp: ``>=1.0.0``
   :depends r-seurat: 
   :requirements:

   :additional platforms:
      

   .. rubric:: Installation

  You need a conda-compatible package manager
  (currently either `micromamba <https://mamba.readthedocs.io>`_, `mamba <https://mamba.readthedocs.io>`_, or `conda <https://docs.conda.io/projects/conda>`_)
  and the Bioconda channel already activated (see :ref:`set-up-channels`).

  While any of above package managers is fine, it is currently recommended to use either
  micromamba or mamba (see `here <https://mamba.readthedocs.io>`_ 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-irisfgm

   and update with::

      mamba update bioconductor-irisfgm

  To create a new environment, run::

      mamba create --name myenvname bioconductor-irisfgm

  with ``myenvname`` being a reasonable name for the environment
  (see e.g. the `mamba docs <https://mamba.readthedocs.io>`_ for details and further options).

  Alternatively, use the docker container::

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

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


.. |downloads_bioconductor-irisfgm| image:: https://img.shields.io/conda/dn/bioconda/bioconductor-irisfgm.svg?style=flat
   :target: https://anaconda.org/bioconda/bioconductor-irisfgm
   :alt:   (downloads)
.. |docker_bioconductor-irisfgm| image:: https://quay.io/repository/biocontainers/bioconductor-irisfgm/status
   :target: https://quay.io/repository/biocontainers/bioconductor-irisfgm
.. _`bioconductor-irisfgm/tags`: https://quay.io/repository/biocontainers/bioconductor-irisfgm?tab=tags


.. raw:: html

    <script>
        var package = "bioconductor-irisfgm";
        var versions = ["1.8.0","1.6.0","1.2.0","1.2.0","1.2.0"];
    </script>






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.. raw:: html
    :file: ../../templates/package_dashboard.html

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