the European Nutrigenomics Organisation Pathway content improvement. How to store an expert’s brain and use it to understand omics. Chris Evelo NuGO WP7 BiGCaT Bioinformatics

the European Nutrigenomics Organisation Understanding  Array data Typical procedure 1.Annotate the reporters with something useful (UniProt!) 2.Sort based on fold change 3.Search for your favorite genes/proteins 4.Throw away 95% of the array

the European Nutrigenomics Organisation

Understanding  Array data Typical procedure 1.Annotate the reporters with something useful (UniProt!) 2.Sort based on fold change 3.Search for your favorite genes/proteins 4.Throw away 95% of the array

the European Nutrigenomics Organisation Understanding  Array data “Advanced” procedures oGene clustering or principal component analysis oGet groups of genes with parallel expression patterns oUseful for diagnosis oNot adding much to understanding (unless combined)

the European Nutrigenomics Organisation Functional Mapping Annotation/ coupling

the European Nutrigenomics Organisation Best known: GenMAPP Full content of GO database Textbook like local mapps Geneboxes with active backpages, coupled to online databases Visualize anything numerical (fold changes on arrays, p-values, present calls, proteomics results)

the European Nutrigenomics Organisation GenMAPP: Full GO content

the European Nutrigenomics Organisation GenMAPP: Textbook like maps Extensive backpages present with links to online databases

the European Nutrigenomics Organisation GenMAPP: visualize anything numerical Example Proteomics results (2D gels with GC-MS identification). Fasting/feeding study shows regulation of glycolysis (data from Johan Renes, UM). Other useful things: - p-values, present calls - presence in clusters - presence in QTLs

the European Nutrigenomics Organisation MAPPfinder Ranks mapps where relatively many changes occur Useful to find unexpected pathways Statistics hardly developed (many dependencies to overcome) Next example from heart failure study (Schroen et al. Circ Res; : )

the European Nutrigenomics Organisation GenMAPP: Full GO content

the European Nutrigenomics Organisation Scientist know GenMapp Advantages: Easy to use, Reasonable visualization Some pathway statistics Interesting content Disadvantages: Small academic initiative, uncertain lifespan No info on reactions, metabolites, location No change (e.g. time course) visualisation

the European Nutrigenomics Organisation IOP gut health comment Nice tool but … Content of the maps is not OK! Improve maps! Starting with fatty acid metabolism.

the European Nutrigenomics Organisation Proposed workflow Combine and forward existing maps to limited group of experts Text mining from key genes/metabolites Forward improved maps to limited group of experts Collect back page info Forward new draft to a larger group of experts within NuGO Develop storage format plus tools Think of best way to store pathway information Develop/adapt entry tools plus converters Test resulting maps Make maps available

the European Nutrigenomics Organisation Text mining Step 1 Ask limited group of experts for map layout and central entities Step 2 Use text mining starting from there Step 3 Combine mining and expert results Expert feedback allows for evaluation of text mining quality.

the European Nutrigenomics Organisation Loosing information GenMapp format does not: -Know about reaction types -Know about reaction input and output -Know about location -Etc… And we will learn a lot about those things

the European Nutrigenomics Organisation GenMapp/BioPAX Expert data Current GenMapp BioPAX Layout data BioPAX plus editor New GenMapp Not a very elegant solution... GenMapp (gene oriented) simply doesn’t fit into BioPAX (reaction centered) And a lot of format specific work… But it does store extra information about interactions, reactions metabolites, localizations etc in BioPAX format.

the European Nutrigenomics Organisation BioPax plus Hinxton meeting with Reactome & GO Expert data Reactome BioPAX Layout data Current GenMapp New GenMapp ?? Using Reactome could allow us to: store everything use high quality entry tools ad an extra round of curation (referees) develop Reactome – BioPAX converters together convince BioPAX about “plus” to work with GenMapp on a more general problem And… use in Reactome itself

the European Nutrigenomics Organisation BioPax plus Adaptation at EBI Expert data Reactome BioPAX Layout data Current GenMapp New GenMapp ?? (EBI/Reactome) will define a way to get Reactome views and export them to GenMapp2

the European Nutrigenomics Organisation BioPAX Plus/GMML 2 Adaptation BiGCaT/GenMapp Expert data Reactome BioPAX GMML Current GenMapp GenMapp 2 NUGO/EBI EBI BiGCaT/GenMapp Rachel van Haaften (BiGCaT/NuGO) and Marjan van Erk (TNO/NuGO) will visit EBI early 2005 to learn doing this Philippe Rocca and Imre Vastrik (EBI/Reactome) will define a way to get Reactome views and export them to GenMapp2 Rachel van Haaften (BiGCaT/NuGO) and Marjan van Erk (TNO/NuGO) will test this and give user feedback BiGCaT students will create GenMapp 2 – GMML converters with help from Lynn Ferrante (GenMapp.org) This step has not been taken care off as of yet… GMML (GenMapp Markup Language) is a superset of BioPAX 1. BioPAX could contain graphical views. (GMML 2 = BioPAX2). But, how doe we make that happen?

the European Nutrigenomics Organisation Participants BiGCaT Bioinformatics Chris Evelo Rachel van Haaften Kitty ter Stege Thomasz Kelder Gijs Huisman TNO Zeist Rob Stierum Marjan van Erk EBI Hinxton Susanna Sansone Philippe Rocca Imre Vastrik GenMAPP.org Lynn Ferrante Bruce Conklin