recipe bioconductor-doppelgangr

Identify likely duplicate samples from genomic or meta-data



GPL (>=2.0)




biotools: doppelgangr, doi: 10.1093/jnci/djw146

The main function is doppelgangR(), which takes as minimal input a list of ExpressionSet object, and searches all list pairs for duplicated samples. The search is based on the genomic data (exprs(eset)), phenotype/clinical data (pData(eset)), and "smoking guns" - supposedly unique identifiers found in pData(eset).

package bioconductor-doppelgangr

(downloads) docker_bioconductor-doppelgangr



depends bioconductor-biobase:


depends bioconductor-biocparallel:


depends bioconductor-impute:


depends bioconductor-summarizedexperiment:


depends bioconductor-sva:


depends r-base:


depends r-digest:

depends r-mnormt:



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-doppelgangr

and update with::

   mamba update bioconductor-doppelgangr

To create a new environment, run:

mamba create --name myenvname bioconductor-doppelgangr

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

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