recipe bioconductor-phenomis

Postprocessing and univariate analysis of omics data

Homepage:

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

License:

CeCILL

Recipe:

/bioconductor-phenomis/meta.yaml

The 'phenomis' package provides methods to perform post-processing (i.e. quality control and normalization) as well as univariate statistical analysis of single and multi-omics data sets. These methods include quality control metrics, signal drift and batch effect correction, intensity transformation, univariate hypothesis testing, but also clustering (as well as annotation of metabolomics data). The data are handled in the standard Bioconductor formats (i.e. SummarizedExperiment and MultiAssayExperiment for single and multi-omics datasets, respectively; the alternative ExpressionSet and MultiDataSet formats are also supported for convenience). As a result, all methods can be readily chained as workflows. The pipeline can be further enriched by multivariate analysis and feature selection, by using the 'ropls' and 'biosigner' packages, which support the same formats. Data can be conveniently imported from and exported to text files. Although the methods were initially targeted to metabolomics data, most of the methods can be applied to other types of omics data (e.g., transcriptomics, proteomics).

package bioconductor-phenomis

versions:

1.4.0-0,  1.2.0-0,  1.0.0-0

depends bioconductor-biobase:

>=2.62.0,<2.63.0

depends bioconductor-biodb:

>=1.10.0,<1.11.0

depends bioconductor-biodbchebi:

>=1.8.0,<1.9.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-multiassayexperiment:

>=1.28.0,<1.29.0

depends bioconductor-multidataset:

>=1.30.0,<1.31.0

depends bioconductor-ropls:

>=1.34.0,<1.35.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-data.table:

depends r-futile.logger:

depends r-ggplot2:

depends r-ggrepel:

depends r-htmlwidgets:

depends r-igraph:

depends r-plotly:

depends r-pmcmrplus:

depends r-ranger:

depends r-rcolorbrewer:

depends r-tibble:

depends r-tidyr:

depends r-venndiagram:

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-phenomis

and update with::

   mamba update bioconductor-phenomis

To create a new environment, run:

mamba create --name myenvname bioconductor-phenomis

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-phenomis:<tag>

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

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