recipe bioconductor-codex

A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing







biotools: codex, doi: 10.1093/nar/gku1363

A normalization and copy number variation calling procedure for whole exome DNA sequencing data. CODEX relies on the availability of multiple samples processed using the same sequencing pipeline for normalization, and does not require matched controls. The normalization model in CODEX includes terms that specifically remove biases due to GC content, exon length and targeting and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data.

package bioconductor-codex

(downloads) docker_bioconductor-codex



depends bioconductor-biostrings:


depends bioconductor-bsgenome.hsapiens.ucsc.hg19:


depends bioconductor-genomeinfodb:


depends bioconductor-iranges:


depends bioconductor-rsamtools:


depends bioconductor-s4vectors:


depends r-base:




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-codex

and update with::

   mamba update bioconductor-codex

To create a new environment, run:

mamba create --name myenvname bioconductor-codex

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

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