recipe r-lipidomer

Create lipidome-wide heatmaps of statistics with the 'lipidomeR'. The 'lipidomeR' provides a streamlined pipeline for the systematic interpretation of the lipidome through publication-ready visualizations of regression models fitted on lipidomics data. With 'lipidomeR', associations between covariates and the lipidome can be interpreted systematically and intuitively through heatmaps, where lipids are categorized by the lipid class and are presented on two-dimensional maps organized by the lipid size and level of saturation. This way, the 'lipidomeR' helps you gain an immediate understanding of the multivariate patterns in the lipidome already at first glance. You can create lipidome-wide heatmaps of statistical associations, changes, differences, variation, or other lipid-specific values. The heatmaps are provided with publication-ready quality and the results behind the visualizations are based on rigorous statistical models.

Homepage:

https://tommi-s.github.io/

License:

GPL3 / GPL-3.0-only

Recipe:

/r-lipidomer/meta.yaml

package r-lipidomer

versions:

0.1.2-2,  0.1.2-1,  0.1.2-0

depends bioconductor-limma:

depends r-base:

>=4.3,<4.4.0a0

depends r-biocmanager:

depends r-dplyr:

depends r-ggplot2:

depends r-knitr:

depends r-reshape2:

depends r-shadowtext:

depends r-stringr:

depends r-tableone:

depends r-tidyr:

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 r-lipidomer

and update with::

   mamba update r-lipidomer

To create a new environment, run:

mamba create --name myenvname r-lipidomer

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/r-lipidomer:<tag>

(see `r-lipidomer/tags`_ for valid values for ``<tag>``)

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