Florian Auer1, Zaynab Hammoud1, Alexandr Ishkin2, Dexter Pratt3, Trey Ideker3,4, Frank Kramer1. 1. Department of Medical Statistics, University Medical Center Göttingen, Göttingen 37099, Germany. 2. Discovery Science, Clarivate Analytics, Boston, MA 02210, USA. 3. Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA. 4. Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA.
Abstract
Motivation: Seamless exchange of biological network data enables bioinformatic algorithms to integrate networks as prior knowledge input as well as to document resulting network output. However, the interoperability between pathway databases and various methods and platforms for analysis is currently lacking. The Network Data Exchange (NDEx) is an open-source data commons that facilitates the user-centered sharing and publication of networks of many types and formats. Results: Here, we present a software package that allows users to programmatically connect to and interface with NDEx servers from within R. The network repository can be searched and networks can be retrieved and converted into igraph-compatible objects. These networks can be modified and extended within R and uploaded back to the NDEx servers. Availability and implementation: ndexr is a free and open-source R package, available via GitHub (https://github.com/frankkramer-lab/ndexr) and Bioconductor (http://bioconductor.org/packages/ndexr/). Contact: florian.auer@med.uni-goettingen.de. Supplementary information: Supplementary data are available at Bioinformatics online.
Motivation: Seamless exchange of biological network data enables bioinformatic algorithms to integrate networks as prior knowledge input as well as to document resulting network output. However, the interoperability between pathway databases and various methods and platforms for analysis is currently lacking. The Network Data Exchange (NDEx) is an open-source data commons that facilitates the user-centered sharing and publication of networks of many types and formats. Results: Here, we present a software package that allows users to programmatically connect to and interface with NDEx servers from within R. The network repository can be searched and networks can be retrieved and converted into igraph-compatible objects. These networks can be modified and extended within R and uploaded back to the NDEx servers. Availability and implementation: ndexr is a free and open-source R package, available via GitHub (https://github.com/frankkramer-lab/ndexr) and Bioconductor (http://bioconductor.org/packages/ndexr/). Contact: florian.auer@med.uni-goettingen.de. Supplementary information: Supplementary data are available at Bioinformatics online.
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