the European Nutrigenomics Organisation Using pathway information to understand omics data Chris Evelo NuGO WP7 BiGCaT Bioinformatics Maastricht

the European Nutrigenomics Organisation Un Oslo Un Munich Un Florence Un Balearic Illes Un Cork Trinity Un. Ulster Rowett Un Newcastle Un Reading IFR DiFE Un Krakow Inserm Marseille TNO Un Wageningen Un Maastricht EBI Nu GOGO GOGO Un Lund Rikilt Rivm

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 Mapping Annotation/ coupling

the European Nutrigenomics Organisation Best known: GenMAPP Free, academic initiative with editable mapps, collaborates with NuGO

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) Update mapps yourself

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 2D gels of 3T3-L1 (pre)-adipocytes Enlarged sections gels derived from: A: 3T3-L1 pre- adipocytes, B: 3T3-L1 adipocytes, C: 3T3-L1 adipocytes with caloric restriction D: 3T3-L1 adipocytes with caloric restriction and TNF-a.

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 Update mapps yourself You can do anything. E.g. add genes, annotation, backpage information, graphics Next page shows a combination of metabolic mapps. “The Nutrigenomics Masterpiece” created by Milka Sokolović (AMC Amsterdam)

the European Nutrigenomics Organisation MAPPfinder Ranks mapps where relatively many changes occur Useful to find unexpected pathways Statistics hardly developed

the European Nutrigenomics Organisation MAPPfinder z-score Number of genes/proteins changed on this mapp Expected number of changes Standard deviation of observed number many dependencies to overcome

the European Nutrigenomics Organisation MAPPfinder 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: Free, Runs on (high end) MS Windows, Relatively easy to use, Reasonable visualization, Some pathway statistics, Interesting content (Including GO, KEGG), Content editable, Adopting standards (e.g. BioPax), Soon to become open source.

the European Nutrigenomics Organisation Scientist know GenMapp Disadvantages: Small academic initiative, uncertain lifespan No info on reactions, metabolites, location No change (e.g. time course) visualization Hard to cope with ambiguous reporters (we are working on that) Content could be better!

the European Nutrigenomics Organisation Metacore example GeneGo, Inc Systems Reconstruction TM Technology

the European Nutrigenomics Organisation AgilentAffymetrixProteomicSAGE Concurrent visualization of different data types

the European Nutrigenomics Organisation GeneGo: primitive view of multiple conditions Can you really see what happens?

the European Nutrigenomics Organisation Build new network using Metacore TM from GeneGO Around p53 protein Making us of biological DB Filtered to reduce complexity: –for ‘rat ortholog’ –for ‘transcriptional regulation’ –for ‘liver’

the European Nutrigenomics Organisation

Filtering needed to reduce complexity

the European Nutrigenomics Organisation

Datasources 1 GenMAPP local MAPPs: Largely created by a single postdoc (Dr.Kam Dahlquist).

the European Nutrigenomics Organisation Datasources 2 KEGG: Older pathway database (Kyoto Japan), on enzyme code (EC) level. Example… The Homo Sapiens Urea cycle Mapp A converted KEGG Mapp Note that not all EC’s were converted and that they don’t have backpages.

the European Nutrigenomics Organisation Datasources 2 KEGG Conversion: = How would you convert EC codes to Swissprot codes? 1)Go to Swissprot, look for EC code 2)Add all proteins with that EC code to GenMapp backpage Example: Superoxide dismutase function reaction would have: Cu/Zn-SOD, Mn-SOD and Ex-SOD in backpage… (and that is not what we usually want. Note that many other tools use KEGG converted pathways (e.g. Spotfire Decissionsite, GeneGo, Ingenuity)

the European Nutrigenomics Organisation Datasources 2 KEGG: Another example: Apoptosis KEGG MappApoptosis KEGG Mapp A contributed Mapp Somebody manually converted this Mapp! Great work… But, there are only four of these

the European Nutrigenomics Organisation Datasources 3 Gene Ontology Database: Simple tree structure database with a of lot biological content (biologist know and like it). Automatic annotation possible even for EST’s See structure in MappFinder (1) (or use Go browser)

the European Nutrigenomics Organisation Datasources 4 Alternative programs like GeneGo: Based on expert knowledge (20 Russian biochemists).

the European Nutrigenomics Organisation NuGO data pathway data collection 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 BioPAX Plus/GMML 2 Working with Reactome, GenMapp and BioPax Expert data Reactome BioPAX GMML Current GenMapp GenMapp 2 NUGO/EBI EBI MDP4/GenMapp With Philippe Rocca and Imre Vastrik (EBI/Reactome) we will define a way to get Reactome views and export them to GenMapp2 BiGCaT students created GenMapp 2 – GMML converters with help from Lynn Ferrante (GenMapp.org) Rachel van Haaften (BiGCaT/NuGO) and Marjan van Erk (TNO/NuGO) visited EBI early 2005 to learn doing this This step has not been taken care off as of yet… Rachel van Haaften (BiGCaT/NuGO) and Marjan van Erk (TNO/NuGO) will test this and give user feedback 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 Can it help you? Seeing the errors and getting useful information A NuGO example Red Wine Polyphenols (Dr Cristina Luceri)

the European Nutrigenomics Organisation Clusters in control group representing pathways Caused by bad technology and bad design

the European Nutrigenomics Organisation After adapted normalization:

the European Nutrigenomics Organisation The bioinformatics BiGCaT Bioinformatics Chris Evelo Rachel van Haaften Arie van Erk Stan Gaj Magali Jaillard Kitty ter Stege Thomasz Kelder Gijs Huisman TNO Zeist Rob Stierum Marjan van Erk EBI Hinxton Susanna Sansone Philippe Rocca Imre Vastrik University Firenze Duccio Cavalieri GenMAPP.org Bruce Conklin Lynn Ferrante

the European Nutrigenomics Organisation The Biology Proteomics Johan Renes (UM) Chris Evelo (BiGCaT) The masterpiece Milka Sokolović (AMC) Wout Lamers (AMC) Magali Jaillard (BiGCaT) Heart Failure Blanche Schroen (UM) Yigal Pinto (UM) Arie van Erk (BiGCaT) Red Wine Polyphenols Cristina Luceri (Firenze) At BiGCaT! RhoA Stolen from Rob Stierum (TNO) Financial contributions: UM, TUe, Senter IOP, WCFS/ICN, Dutch Heart Foundation, NuGO