:orphan: .. only available via index, not via toctree .. title:: Package Recipe 'bioconductor-viseago' .. highlight: bash bioconductor-viseago ==================== .. conda:recipe:: bioconductor-viseago :replaces_section_title: :noindex: ViSEAGO\: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity :homepage: https://bioconductor.org/packages/3.18/bioc/html/ViSEAGO.html :license: GPL-3 :recipe: /`bioconductor-viseago `_/`meta.yaml `_ The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology \(GO\) analysis of complex experimental design with multiple comparisons of interest. It allows to study large\-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis\: Visualization\, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations\, which are retrieved from one of NCBI EntrezGene\, Ensembl or Uniprot databases for several species. Using available R packages and novel developments\, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists\, enhancing reporting capabilities while maintaining reproducibility. .. conda:package:: bioconductor-viseago |downloads_bioconductor-viseago| |docker_bioconductor-viseago| :versions: .. raw:: html
1.24.0-01.16.0-01.14.0-01.12.0-01.8.0-01.6.0-01.4.0-11.4.0-01.2.0-0 ``1.24.0-0``,  ``1.16.0-0``,  ``1.14.0-0``,  ``1.12.0-0``,  ``1.8.0-0``,  ``1.6.0-0``,  ``1.4.0-1``,  ``1.4.0-0``,  ``1.2.0-0``,  ``1.0.0-0`` .. raw:: html
:depends on bioconductor-annotationdbi: ``>=1.72.0,<1.73.0`` :depends on bioconductor-annotationforge: ``>=1.52.0,<1.53.0`` :depends on bioconductor-biomart: ``>=2.66.0,<2.67.0`` :depends on bioconductor-complexheatmap: ``>=2.26.0,<2.27.0`` :depends on bioconductor-fgsea: ``>=1.36.0,<1.37.0`` :depends on bioconductor-go.db: ``>=3.22.0,<3.23.0`` :depends on bioconductor-gosemsim: ``>=2.36.0,<2.37.0`` :depends on bioconductor-topgo: ``>=2.62.0,<2.63.0`` :depends on r-base: ``>=4.5,<4.6.0a0`` :depends on r-circlize: :depends on r-data.table: :depends on r-dendextend: :depends on r-diagrammer: :depends on r-dt: :depends on r-dynamictreecut: :depends on r-ggplot2: :depends on r-heatmaply: :depends on r-htmlwidgets: :depends on r-igraph: :depends on r-plotly: :depends on r-r.utils: :depends on r-rcolorbrewer: :depends on r-scales: :depends on r-upsetr: :additional platforms: Installation ------------ You need a conda-compatible package manager (currently either `pixi `__, `conda `__, or `micromamba `__) and the Bioconda channel already activated (see :ref:`bioconda_setup`). 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 :ref:`bioconda_setup`), to install globally, run:: pixi global install bioconductor-viseago to add into an existing workspace instead, run:: pixi add bioconductor-viseago 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 :ref:`bioconda_setup`), to install into an existing and activated environment, run:: conda install bioconductor-viseago Alternatively, to install into a new environment, run:: conda create -n envname bioconductor-viseago 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-viseago: (see `bioconductor-viseago/tags`_ for valid values for ````). 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. .. _conda: https://conda.io .. _pixi: https://pixi.sh .. |downloads_bioconductor-viseago| image:: https://img.shields.io/conda/dn/bioconda/bioconductor-viseago.svg?style=flat :target: https://anaconda.org/bioconda/bioconductor-viseago :alt: (downloads) .. |docker_bioconductor-viseago| image:: https://quay.io/repository/biocontainers/bioconductor-viseago/status :target: https://quay.io/repository/biocontainers/bioconductor-viseago .. _`bioconductor-viseago/tags`: https://quay.io/repository/biocontainers/bioconductor-viseago?tab=tags .. raw:: html Download stats ----------------- .. raw:: html :file: ../../templates/package_dashboard.html Link to this page ----------------- Render an |install-with-bioconda| 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-viseago/README.html) .. |install-with-bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/bioconductor-viseago/README.html