recipe bioconductor-metnet

MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two matrices are combined to form a adjacency matrix inferred from both quantitative and structure information.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/MetNet.html

License

GPL-2

Recipe

/bioconductor-metnet/meta.yaml

package bioconductor-metnet

(downloads) docker_bioconductor-metnet

Versions

1.0.0-0

Depends
Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-metnet

and update with:

conda update bioconductor-metnet

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-metnet:<tag>

(see bioconductor-metnet/tags for valid values for <tag>)