recipe bioconductor-cfdnapro

cfDNAPro extracts and Visualises biological features from whole genome sequencing data of cell-free DNA






cfDNA fragments carry important features for building cancer sample classification ML models, such as fragment size, and fragment end motif etc. Analyzing and visualizing fragment size metrics, as well as other biological features in a curated, standardized, scalable, well-documented, and reproducible way might be time intensive. This package intends to resolve these problems and simplify the process. It offers two sets of functions for cfDNA feature characterization and visualization.

package bioconductor-cfdnapro

(downloads) docker_bioconductor-cfdnapro



depends bioconductor-biocgenerics:


depends bioconductor-bsgenome.hsapiens.ncbi.grch38:


depends bioconductor-bsgenome.hsapiens.ucsc.hg19:


depends bioconductor-bsgenome.hsapiens.ucsc.hg38:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-plyranges:


depends bioconductor-rsamtools:


depends r-base:


depends r-dplyr:


depends r-ggplot2:


depends r-magrittr:


depends r-quantmod:


depends r-rlang:


depends r-stringr:


depends r-tibble:



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-cfdnapro

and update with::

   mamba update bioconductor-cfdnapro

To create a new environment, run:

mamba create --name myenvname bioconductor-cfdnapro

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

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