recipe r-mixkernel

Kernel-based methods are powerful methods for integrating heterogeneous types of data. mixKernel aims at providing methods to combine kernel for unsupervised exploratory analysis. Different solutions are provided to compute a meta-kernel, in a consensus way or in a way that best preserves the original topology of the data. mixKernel also integrates kernel PCA to visualize similarities between samples in a non linear space and from the multiple source point of view. Functions to assess and display important variables are also provided in the package. Jerome Mariette and Nathalie Villa-Vialaneix (2017) <doi:10.1093/bioinformatics/btx682>.

Homepage:

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

License:

GPL3 / GPL (>= 2)

Recipe:

/r-mixkernel/meta.yaml

package r-mixkernel

versions:

0.9-0,  0.8-2,  0.8-1,  0.8-0,  0.7-0,  0.6-0,  0.5-2,  0.5-1,  0.5-0, 

0.9-0,  0.8-2,  0.8-1,  0.8-0,  0.7-0,  0.6-0,  0.5-2,  0.5-1,  0.5-0,  0.4-2,  0.4-1,  0.4-0,  0.3-1,  0.3-0

depends bioconductor-mixomics:

depends bioconductor-phyloseq:

depends r-base:

>=4.3,<4.4.0a0

depends r-corrplot:

depends r-ggplot2:

depends r-ldrtools:

depends r-markdown:

depends r-matrix:

depends r-psych:

depends r-quadprog:

depends r-reticulate:

>=1.14

depends r-vegan:

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 r-mixkernel

and update with::

   mamba update r-mixkernel

To create a new environment, run:

mamba create --name myenvname r-mixkernel

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-mixkernel:<tag>

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

Download stats

Link to this page

Render an 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/r-mixkernel/README.html)