Transcript Pathway data flow how to pick experts brains and use it

Nu GO
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
Nu GO
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
Nu GO
the European Nutrigenomics Organisation
Nu GO
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
Nu GO
Understanding Array data
“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)
the European Nutrigenomics Organisation
Nu GO
Functional Mapping
Annotation/
coupling
the European Nutrigenomics Organisation
Nu GO
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
Nu GO
GenMAPP: Full GO content
the European Nutrigenomics Organisation
Nu GO
GenMAPP:
Textbook like maps
Extensive
backpages
present with
links to online
databases
the European Nutrigenomics Organisation
GenMAPP: visualize
Nu GO 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
Nu GO
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)
the European Nutrigenomics Organisation
Nu GO
GenMAPP: Full GO content
the European Nutrigenomics Organisation
Nu GO
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
Nu GO
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
Nu GO
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
Think of best way to store
pathway information
Develop storage format
plus tools
Collect back page info
Forward new draft to a
larger group of experts
within NuGO
Develop/adapt entry tools
plus converters
Test resulting maps
Make maps available
the European Nutrigenomics Organisation
Nu GO
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
Nu GO
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
Nu GO
GenMapp/BioPAX
Not a very elegant solution...
Current GenMapp
GenMapp (gene oriented)
simply doesn’t fit into
BioPAX (reactionBioPAX
centered)
BioPAX plus editor
And a lot of format specific work…
Layout data
But it does store extra information
about interactions, reactions
Expert datametabolites, localizations
New
etcGenMapp
in BioPAX format.
the European Nutrigenomics Organisation
Nu GO
Hinxton meeting with
Reactome & GO
Using Reactome
Current GenMapp
could allow us to:
• store everything
• use high quality entry tools
Expert data
• ad an extra round of curation
And…
(referees)
use in Reactome
• develop Reactome – BioPAX
itself
BioPAX
converters together
Reactome
• convince BioPAX about BioPax
“plus” plus
??
Layout data
• to work with GenMapp on a more
general problem
New GenMapp
the European Nutrigenomics Organisation
Nu GO
Adaptation at EBI
Current GenMapp
Expert data
BioPAX
Reactome
BioPax plus
??
(EBI/Reactome) will
define a way to get
Reactome views and
export them to
GenMapp2
Layout data
New GenMapp
the European Nutrigenomics Organisation
Adaptation
Rachel van Haaften
BiGCaT/GenMapp
and
Nu GO(BiGCaT/NuGO)
Marjan van Erk Rachel van Haaften
(TNO/NuGO) will test
This
step hasand
not
(BiGCaT/NuGO)
GMML (GenMapp
Markup
this and give user been
taken
Marjan
van care
Erk off
Language)
is a superset
of
Current
GenMapp
feedback
as of yet…
(TNO/NuGO)
will
BioPAX 1. BioPAX
could
visitviews.
EBI early 2005
contain graphical
toBiGCaT
learn doing
this
Expert
data 2 = BioPAX2).
(GMML
students
BioPAX
will create
GenMapp
Philippe
Rocca and
But, how doe we make
2 – GMML
Imre Vastrik
BioPAX Plus/GMML 2
that happen?
NUGO/EBI
converters
with help
(EBI/Reactome)
will
from Lynn
Ferrante
define
a way to get
(GenMapp.org)
Reactome views andGMML
Reactome
export them to
GenMapp2
EBI
BiGCaT/GenMapp
GenMapp 2
the European Nutrigenomics Organisation
Nu GO
Participants
BiGCaT Bioinformatics
• Chris Evelo
• Rachel van Haaften
• Kitty ter Stege
• Thomasz Kelder
• Gijs Huisman
EBI Hinxton
• Susanna Sansone
• Philippe Rocca
• Imre Vastrik
TNO Zeist
• Rob Stierum
• Marjan van Erk
GenMAPP.org
• Lynn Ferrante
• Bruce Conklin
the European Nutrigenomics Organisation