recipe r-statvisual

Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.

Homepage:

https://CRAN.R-project.org/package=statVisual

License:

GPL3 / GPL (>= 2)

Recipe:

/r-statvisual/meta.yaml

package r-statvisual

(downloads) docker_r-statvisual

versions:

1.2.1-51.2.1-41.2.1-31.2.1-21.2.1-11.2.1-01.1.9-01.1.8-0

depends bioconductor-biobase:

depends bioconductor-limma:

depends bioconductor-pvca:

depends r-base:

>=4.3,<4.4.0a0

depends r-dplyr:

depends r-factoextra:

depends r-forestplot:

depends r-gbm:

depends r-ggally:

depends r-ggdendro:

depends r-ggfortify:

depends r-ggplot2:

depends r-ggrepel:

depends r-glmnet:

depends r-gplots:

depends r-gridextra:

depends r-knitr:

depends r-magrittr:

depends r-multigroup:

depends r-pheatmap:

depends r-proc:

depends r-randomforest:

depends r-rcolorbrewer:

depends r-reshape2:

depends r-rmarkdown:

depends r-rpart.plot:

depends r-tibble:

depends r-tidyverse:

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-statvisual

and update with::

   mamba update r-statvisual

To create a new environment, run:

mamba create --name myenvname r-statvisual

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-statvisual:<tag>

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

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