recipe bioconductor-poma

Tools for Omics Data Analysis

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-poma/meta.yaml

A reproducible and easy-to-use toolkit for visualization, pre-processing, exploration, and statistical analysis of omics datasets. The main aim of POMA is to enable a flexible data cleaning and statistical analysis processes in one comprehensible and user-friendly R package. This package has a Shiny app version called POMAShiny that implements all POMA functions. See https://github.com/pcastellanoescuder/POMAShiny. See Castellano-Escuder P, González-Domínguez R, Carmona-Pontaque F, et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.

package bioconductor-poma

versions:

1.12.0-0,  1.10.0-0,  1.8.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-2,  1.0.0-1

depends bioconductor-complexheatmap:

>=2.18.0,<2.19.0

depends bioconductor-deseq2:

>=1.42.0,<1.43.0

depends bioconductor-impute:

>=1.76.0,<1.77.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-mixomics:

>=6.26.0,<6.27.0

depends bioconductor-rankprod:

>=3.28.0,<3.29.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-broom:

depends r-caret:

depends r-dbscan:

depends r-dplyr:

depends r-ggplot2:

depends r-ggrepel:

depends r-glasso:

>=1.11

depends r-glmnet:

depends r-magrittr:

depends r-randomforest:

depends r-rmarkdown:

depends r-tibble:

depends r-tidyr:

depends r-uwot:

depends r-vegan:

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-poma

and update with::

   mamba update bioconductor-poma

To create a new environment, run:

mamba create --name myenvname bioconductor-poma

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-poma:<tag>

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

Download stats

Link to this page

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