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Metabopolis

Metabopolis is a new layout algorithm for biological pathways, which has been developed by Hsiang-Yun Wu, Martin Nöllenburg, Filipa Sousa, and Ivan Viola, in the group Research Division of Computer Graphics at TU Wien in Vienna, Austria. The c++ library was developed by Hsiang-Yun Wu.

How to cite?

Hsiang-Yun Wu, Martin Nöllenburg, Filipa L. Sousa, and Ivan Viola, Metabopolis: Scalable Network Layout for Biological Pathway Diagrams in Urban Map Style, BMC Bioinformatics, Vol. 20, No. 1, p. 187, 2019. Paper: http://doi.org/10.1186/s12859-019-2779-4 Video: https://www.youtube.com/watch?v=AhWCIGTxqAg

Installing

Prerequisites

Metabopolis

Clone the Metabopolis repository into a directory METABOPOLIS.

$ cd METABOPOLIS
$ mkdir build
$ cd build
$ cmake ../
$ make

Tested environment

  • Ubuntu 16.04 LTS
  • Mac OS 10.12

Using Metabopolis

$ ./metabopolis

Step 1: Select the target folder of a dataset by pressing button "Browse" Defined: User defined duplicated metabolites. Duplication of metabolites is defined from ~/Desktop/gitroot/tools/bionet/xml/metabolite_frequency.txt Threshold: User defined threshold for metabolites duplication

Step 2: Edit the relationship graph Delete an edge: Shift Key + Mouse Right Button on an Edge Add an edge: Shift Key + Mouse Left Button on one Node and the other Confirm button: Compute graph layout Adjust button: Adjust box size

Step 3: Compute button: Compute the orthogonal layout HOLA: human-like orthogonal layout yFiles: compact orthogonal algorithm from yFiles package

Step 4: Compute button: Compute the connectivity between nodes in different categories

Step 5: Interaction mode Local: Connection of metabolites in one category Global: Connection of metabolites in multiples categories Both: Both Bundled: Bundled edges Extended: Extended edges

Remarks:

  • After loading the file folder, press "Batch" to run the program with all default settings.
  • Press "Export" to export images, which will be stored at METABOPOLIS/svg/

Acknowledgement

The project leading to this submission has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985 and from the Vienna Science and Technology Fund (WWTF) through project VRG11-010.

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Biological Pathway Visualization

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