recipe bioconductor-spiky

Spike-in calibration for cell-free MeDIP






spiky implements methods and model generation for cfMeDIP (cell-free methylated DNA immunoprecipitation) with spike-in controls. CfMeDIP is an enrichment protocol which avoids destructive conversion of scarce template, making it ideal as a "liquid biopsy," but creating certain challenges in comparing results across specimens, subjects, and experiments. The use of synthetic spike-in standard oligos allows diagnostics performed with cfMeDIP to quantitatively compare samples across subjects, experiments, and time points in both relative and absolute terms.

package bioconductor-spiky

(downloads) docker_bioconductor-spiky



depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rsamtools:


depends bioconductor-s4vectors:


depends r-bamlss:

depends r-base:


depends r-blandaltmanleh:

depends r-ggplot2:

depends r-scales:



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-spiky

and update with::

   mamba update bioconductor-spiky

To create a new environment, run:

mamba create --name myenvname bioconductor-spiky

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

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