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. 2012 Jan 31:13:20.
doi: 10.1186/1471-2105-13-20.

graphite - a Bioconductor package to convert pathway topology to gene network

Gabriele Sales  1 , Enrica Calura, Duccio Cavalieri, Chiara Romualdi
Affiliations

graphite - a Bioconductor package to convert pathway topology to gene network

Gabriele Sales et al. BMC Bioinformatics. .

Abstract

Background: Gene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses.Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families.

Results: Here we present graphite, a Bioconductor package addressing these issues. Pathway information from four different databases is interpreted following specific biologically-driven rules that allow the reconstruction of gene-gene networks taking into account protein complexes, gene families and sensibly removing chemical compounds from the final graphs. The resulting networks represent a uniform resource for pathway analyses. Indeed, graphite provides easy access to three recently proposed topological methods. The graphite package is available as part of the Bioconductor software suite.

Conclusions: graphite is an innovative package able to gather and make easily available the contents of the four major pathway databases. In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements.

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Figures

Figure 1
Figure 1
Edges and nodes distribution of networks after pathway conversion according to the selected database.
Figure 2
Figure 2
Toy examples of nodes with multiple elements converted to gene-network. Group AND (protein complexes, Panel A), group OR (member of gene family, Panel B) and compound mediated signal (panel C).
Figure 3
Figure 3
Differences in signal reconstruction of a selected portion of the insulin signaling pathway of KEGG (hsa04910). Panel A. The original signal cascade. Panel B. graphite signal reconstruction through chemical compound propagation. Numbers represent EntrezGene IDs. Panel C. KEGGgraph signal reconstruction.
Figure 4
Figure 4
Catalysis and cleavage of Notch 1 by Gamma Secretase Complex. Reactome representation of the reactions (Panel A), BioPax information as it is stored in owl model and in Cytoscape plug-in BioPax dedicated (respectively panel B and C) and the graphite final network (panel D).
Figure 5
Figure 5
Visualization of graphite network using RCytoscape package.
Figure 6
Figure 6
Results of the simulation study on the Insulin signaling pathway compound mediated signal propagation. Panel A. Signal paths selected to be differentially expressed. Panel B. p-value distribution of the topological analysis SPIA (pPERT) with and without propagation. Panel C. graphite network obtained from insulin pathway with propagation. Panel D. network obtained from insulin pathway without propagation.
Figure 7
Figure 7
Visualization of the chronic myeloid leukemia network of graphite, that contain BCR and ABL1 genes. Colors represent up or down regulated genes between positive and negative BCR/ABL rearrangement.
See this image and copyright information in PMC

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