Department of Bioinformatics, Maastricht University

Biological Data Visualization on Pathways and Networks

Martina Kutmon1,2, Anwesha Bohler1,2, Susan L. Coort1, Alexander R. Pico3, Chris T. Evelo1,2

1 Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, the Netherlands 2 Netherlands Consortium for System Biology 3 Gladstone Institute of Cardiovascular Disease, San Francisco, California, USA

Visualization of data on biological pathways

Multi-omics data: Transcriptomics, proteomics, metabolomics, fluxomics

Correspondence to:

Martina Summer-Kutmon, PhD student

martina.kutmon@rmaastrichtuniversity.nl

+31 43 38 81187

Department of Bioinformatics - BiGCaT

NUTRIM School for Nutrition, Toxicology and Metabolism

Maastricht University

P.O. Box 616

6200 MD Maastricht, The Netherlands

PathVisio / WikiPathways:

http://www.pathvisio.org http://www.wikipathways.org

Cytoscape:

http://www.cytoscape.org http://apps.cytoscape.org

Tools

PathVisio (www.pathvisio.org) is an open source pathway tool to edit,

visualize and analyse biological pathways. The visualization options are

designed to allow highly complex data visualization relevant in pathway

analysis.

Cytoscape (www.cytoscape.org) is an open source network analysis and

visualization tool. Visualization styles provide a wide variety of options to

visualize many types of different data on networks.

Challenges:

In pathways and networks:

– Visualization of

genetic variation data

phosphorylation data

methylation data

In networks:

– Hairball networks – highlight important parts in the network

– Multiple data sets in one network (e.g. time-series, multiple experiments,...)

e.g. phosphorylation sites

Visualization of data on biological networks

WikiPathways app in Cytoscape: Open a pathway as a network

Advanced Visualization Options in PathVisio

Visualize multiple datasets or time series data on pathway elements in

biological pathways. Gradient-based and rule-based visualization styles

are supported.

Flexible Visualization Styles in Cytoscape

Change node/edge color, shape, size, etc. Use edge-bundeling for large networks.

Apply continuous, discrete and/or passthrough mapping for data visualization.