recipe bioconductor-linkhd

LinkHD: a versatile framework to explore and integrate heterogeneous data






Here we present Link-HD, an approach to integrate heterogeneous datasets, as a generalization of STATIS-ACT (“Structuration des Tableaux A Trois Indices de la Statistique–Analyse Conjointe de Tableaux”), a family of methods to join and compare information from multiple subspaces. However, STATIS-ACT has some drawbacks since it only allows continuous data and it is unable to establish relationships between samples and features. In order to tackle these constraints, we incorporate multiple distance options and a linear regression based Biplot model in order to stablish relationships between observations and variable and perform variable selection.

package bioconductor-linkhd

(downloads) docker_bioconductor-linkhd



depends bioconductor-multiassayexperiment:


depends r-base:


depends r-cluster:

depends r-data.table:

depends r-emmeans:

depends r-ggplot2:

depends r-ggpubr:

depends r-gridextra:

depends r-reshape2:

depends r-rio:

depends r-scales:

depends r-vegan:



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-linkhd

and update with::

   mamba update bioconductor-linkhd

To create a new environment, run:

mamba create --name myenvname bioconductor-linkhd

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<tag>

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

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