recipe bioconductor-iasva

Iteratively Adjusted Surrogate Variable Analysis






Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the unmodeled variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.

package bioconductor-iasva

(downloads) docker_bioconductor-iasva



depends bioconductor-biocparallel:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-cluster:

depends r-irlba:



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-iasva

and update with::

   mamba update bioconductor-iasva

To create a new environment, run:

mamba create --name myenvname bioconductor-iasva

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-iasva/tags`_ for valid values for ``<tag>``)

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