• InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation

      Breuer, Karin; Foroushani, Amir K.; Laird, Matthew R; Chen, Carol; Sribnaia, Anastasia; Lo, Raymond; Winsor, Geoffrey L; Hancock, Robert E.W.; Brinkman, Fiona S. L.; Lynn, David J; et al. (Oxford University Press, 2012-11-24)
      InnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.
    • Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures

      Foroushani, Amir B. K.; Brinkman, Fiona S. L.; Lynn, David J; Teagasc Walsh Fellowship Programme; AllerGen 12B&B2; Genome Canada; Michael Smith Foundation for Health Research; RMIS6018 (PeerJ, 2013-12-19)
      Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/.