Pathways for exploratory data analysis.

<p>Biological pathways are powerful visualization tools for data exploration, focused on finding the right question.</p

WikiPathways can be accessed by end-users from the wiki-style website.

<p>In addition, the WikiPathways web service provides a programmatic interface that can be used in many programming languages, including R, python, Java and perl and in workflow tools such as Taverna. Using this interface, new pathway analysis tools can be built and existing bioinformatics tools can be extended with pathway-based functionality.</p

Web application that integrates pathways with gene expression information.

<p>Pathway and gene expression information are retrieved from the WikiPathways and ArrayExpress Atlas web services respectively. A Java servlet integrates this information and publishes it to an interactive web application. In this web application, users can view the information on an interactive pathway diagram.</p

Transitive dependency structure of PathVisio 3.

<p>The application consists of eight modules each providing specific functionality. The modules <i>core</i> and <i>data</i> are independent modules (colored in blue) that function as libraries that can be reused outside of PathVisio (PV). Especially the <i>core</i> module is often used as a PV library for reading and writing of pathway files. Other modules in red, <i>gui</i>, <i>desktop</i> and <i>visualization</i>, provide functionality that is used by other modules. Green modules, <i>gex</i>, <i>statistics</i> and <i>plugin manager</i>, are not used by other PV modules but can be used by PV plugins. The PV JavaApplet version integrated in WikiPathways uses the <i>core</i> and <i>gui</i> modules.</p

Plugin extension and installation system of PathVisio 3.

<p>The plugin repository stores all plugin files and their dependencies. The RepoIndex library is used to create a repository.xml file which contains the dependency indexes of all plugins. Metadata about plugins is stored in the PathVisio plugin database which is then exported into a pathvisio.xml file. The PathVisio 3 plugin manager retrieves data from both files to facilitate the installation of plugins in PathVisio 3.</p

The colored boxes represent genes which are up (red) or down (blue) regulated in diabetes mellitus.

<p>PIK3R2, MYO1C, PRKAA2, LIPE are down regulated in pre-diabetes. STX4A is down regulated in type 1 diabetes longstanding. PRKCQ, PTPN11, FOXO3A are down regulated in type 2 diabetes. GAB1, RHEB, MAP4K4, SNAP23 are up regulated in pre-diabetes. RHOJ, PRKCB are up regulated in type 1 diabetes recent onset. MAPK14UP, EIF4EBP1 are up regulated in type 1 diabetes clinical onset. From these 17 up or down regulated genes, 9 are being reported as being in the top 10 disease and phenotype associations for the selected gene in DisGeNET (i.e. PIK3R2, PRKAA2, LIPE, STX4A, PRKCQ, FOXO3A, MAP4K4, SNAP23, and PRKCB) (Gene-disease association data were retrieved from the DisGeNET Database, GRIB/IMIM/UPF Integrative Biomedical Informatics Group, Barcelona. (<a href="http://www.disgenet.org/" target="_blank">http://www.disgenet.org/</a>). 04, 2016)</p

Pathway statistics result in PathVisio.

<p>The user defines the criterion for significantly changed genes with an absolute log2FC > 1 (A). A Z-Score is calculated for each pathway in the pathway collection and in the result table the pathways are ranked based on their Z-Score (B). A high Z-Score indicates that the pathway is more affected than expected based on the overall dataset. The user can click on each pathway to open the pathway with the data visualized on it.</p

PathVisio 3, a full-powered pathway editor.

<p>(A) The basic drawing palette contains data nodes, interactions, graphical elements, cellular compartments and a few templates. Simple drag-and-drop mechanism allows users to add the elements in the pathway diagram. (B) The ACE inhibitor pathway on WikiPathways (<a href="http://www.wikipathways.org/instance/WP554" target="_blank">http://www.wikipathways.org/instance/WP554</a>) was drawn in PathVisio describing the downstream effects of angiotensin-converting-enzyme (ACE) inhibtors. (C) The entities and interactions in the pathways can be annotated with external identifiers. In this example the pathway author annotated the <i>KNG1</i> gene with the Entrez Gene identifier 3827. PathVisio utilizes the BridgeDb identifier mapping framework to free the user from manual identifier mapping steps.</p

Multi-omics visualization in PathVisio.

<p>Two transcriptomics datasets are visualized together with a metabolomics dataset on the Kennedy pathway from WikiPathways (<a href="http://www.wikipathways.org/instance/WP1771" target="_blank">http://www.wikipathways.org/instance/WP1771</a>). The log2FC is visualized in the first column of the data node boxes using a gradient from blue over white to red. In the second column three levels of p-values are visualized (p-value < 0.01, < 0.05 and > 0.05). The expression data for a selected gene or metabolite is shown in the “Data” tab on the right side. In the red rectangle the expression data for the selected <i>Cept1</i> gene is shown. There are two measurements for the gene from the two transcriptomics datasets, therefore the gene box in the pathway is split horizontally into two rows.</p

Example queries handled by the WikiPathways SPARQL endpoint.

<p>Example queries handled by the WikiPathways SPARQL endpoint.</p