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

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.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.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.A great deal of effort has been recently directed towards the study of gene sets (hereafter GSA) in the context of microarray data analysis. The aim is to identify groups of functionally related genes with possibly moderate, but coordinated, expression changes. Several GSA tests, both univariate and multivariate, have been recently developed. See [1] for a comprehensive review, and [2-4] for a detailed description and a critical investigation of the tested hypotheses.These approaches, although effective, miss the information of the topological properties of the pathways. To this end, the seminal paper by Draghici et al. [5] proposed a radically different approach (called impact analysis, SPIA) attempting to capture several aspects of the data: the fold change of differentially expressed genes (DEGs), the pathway enrichment and the topology of signaling pathw