Genoscape

Category Genomics>Gene Expression Analysis/Profiling/Tools

Abstract Genoscape is an open-source Cytoscape plug-in that visually integrates gene expression data sets from GenoScript, a transcriptomic database, and KEGG pathways into Cytoscape networks.

The generated visualization highlights gene expression changes and their statistical significance.

The plug-in also allows one to browse GenoScript or import transcriptomic data from other sources through tab-separated text files.

Genoscape has been successfully used by researchers to investigate the results of ‘gene expression profiling’ experiments.

Genoscape was developed for biologists to automate the process of locally:

1) Retrieving statistically analyzed expression data from GenoScript;

2) Retrieving biological pathways from the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG);

3) Integrating those data into Cytoscape (see G6G Abstract Number 20092); and

4) Modifying the visualization to highlight the level and significance of expression ratio values.

Genoscape System Overview --

Genoscape allows users to browse the ‘GenoScript database’ over a network connection and select transcriptomic data to be imported into Cytoscape. A tab-separated text file can also be used as the input.

Genoscape automatically maps most gene or gene product identifiers to KEGG identifiers, enabling the import of expression data from various sources.

When importing KEGG pathways, elements are filtered in order to keep only those nodes corresponding to genes or enzymes.

Moreover, additional ‘gene nodes’ are created when KEGG pathway elements represent enzyme or protein complexes, in order to unambiguously integrate individual gene expression data.

Using Genoscape, KEGG pathways are displayed as Cytoscape networks.

Each pathway element is represented as a node. Genoscape generates a visualization style that highlights gene expression changes and their statistical significance.

Cytoscape graphs produced by Genoscape can be visualized, laid out, modified, and saved in various ways using the built-in Cytoscape features, such as filtering options, or one of the automatic layout algorithms.

Genoscape Methods and Implementation --

Genoscape was implemented in Java as a Cytoscape plug-in. GenoScript relies on a SQL relational database and implements a login procedure to ensure data privacy.

All Genoscape data requests are performed through a Common Gateway Interface (CGI). This layer was developed to manage and secure access to the GenoScript database as the user cannot be directly connected to the relational database.

Data import from GenoScript to Cytoscape is performed using specific XML and tab-separated text formats. The tab-separated text format is used to transfer expression data.

The XML format is used to browse GenoScript from Cytoscape, as it encloses the relational organization of experiments and analyses in the GenoScript database.

KEGG pathways and the mapping of KEGG identifiers to external references are retrieved via the KEGG FTP server.

Several tab-separated text files are generated: one for each pathway and one for the pathway list.

To avoid unnecessary requests, pathway data are saved locally, improving the plug-in efficiency in subsequent runs.

The correspondence between KEGG pathway elements and a GenoScript or user-generated gene list is automatically achieved by scanning KEGG identifier mapping tables, which include identifiers such as KEGG, Entrez-gene, Ensembl or other widely used species- specific identifiers.

To update the visualization according to expression level changes, Genoscape builds a dedicated customizable VisualStyle that maps the expression data to visual properties.

Genoscape Use Case --

Genoscape has been successfully used to explore ‘expression data’ of the eukaryotic organism Entamoeba histolytica.

Entamoeba histolytica is the causative agent of Amoebiasis, a parasitic infection of the human intestine and liver.

Transcription profiles of the parasite under stress conditions were determined and genes involved in stress response were identified using DNA microarrays.

Genoscape allowed the identification of pathways containing modulated genes, facilitating the analysis of networks and opening up new avenues for studies in basic biology, diagnosis of infectious diseases, and drug development.

System Requirements

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Manufacturer

Manufacturer Web Site Genoscape

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G6G Abstract Number 20508

G6G Manufacturer Number 104127