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

the European Nutrigenomics Organisation

NuNuGOGONuNuGOGO

Pathway content improvement.How to store an expert’s brain

and use it to understand omics.

Chris EveloNuGO WP7

BiGCaT Bioinformatics


NuNuGOGONuNuGOGO 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


NuNuGOGONuNuGOGO



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



“Advanced” procedures

o Gene clustering or principal component analysis

o Get groups of genes with parallel expression patterns

o Useful for diagnosis

o Not adding much to understanding (unless combined)


NuNuGOGONuNuGOGO Functional Mapping

Annotation/coupling


NuNuGOGONuNuGOGO 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)


NuNuGOGONuNuGOGO GenMAPP: Full GO content


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GenMAPP:Textbook like maps

Extensive backpages

present with links to

online databases


NuNuGOGONuNuGOGO

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


NuNuGOGONuNuGOGO 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; 2004 95: 506-514)


NuNuGOGONuNuGOGO GenMAPP: Full GO content


NuNuGOGONuNuGOGO 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


NuNuGOGONuNuGOGO IOP gut health comment

Nice tool but …

Content of the maps is not OK!

Improve maps! Starting with fatty acid metabolism.


NuNuGOGONuNuGOGO Proposed workflowCombine and forward

existing mapsto limited group of experts

Text miningfrom key genes/metabolites

Forward improved mapsto limited group of experts

Collect back page info

Forward new draft to alarger group of experts

within NuGO

Develop storage format plus tools

Think of best way to storepathway information

Develop/adapt entry toolsplus converters

Test resulting maps

Make maps available


NuNuGOGONuNuGOGO Text mining

Step 1Ask limited group of experts for map layout and central entities

Step 2Use text mining starting from there

Step 3Combine mining and expert results

Expert feedback allows for evaluation of text mining quality.


NuNuGOGONuNuGOGO 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


NuNuGOGONuNuGOGO 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 intoBioPAX (reaction centered)

And a lot of format specific work…

But it does store extra informationabout interactions, reactions metabolites, localizations etc

in BioPAX format.


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BioPax plus

Hinxton meeting with Reactome & GO

Expert data

ReactomeBioPAX

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


NuNuGOGONuNuGOGO

BioPax plus

Adaptation at EBI

Expert data

ReactomeBioPAX

Layout data

Current GenMapp

New GenMapp

??

(EBI/Reactome) will define a way to get Reactome views and export

them to GenMapp2


NuNuGOGONuNuGOGO

BioPAX Plus/GMML 2

Adaptation BiGCaT/GenMapp

Expert data

Reactome

BioPAX

GMML

Current GenMapp

GenMapp 2

NUGO/EBI

EBIBiGCaT/GenMapp

Rachel van Haaften

(BiGCaT/NuGO) and Marjan van Erk (TNO/NuGO)

will visit EBI early 2005 to

learn doing thisPhilippe 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?


NuNuGOGONuNuGOGO 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

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

Documents

limited group of experts

group of expertstext

existing maps

use text mining

larger group of experts

pathway content improvement

group of expertscollect

genmappfull content