Transcript MGED Ontology Working Group

The MGED Ontology Is An
Experimental Ontology
Bio-Ontologies Aug 8, 2002
Chris Stoeckert, Helen Parkinson
and the
MGED Ontology Working Group
MGED Mission Statement
• The Microarray Gene Expression Data (MGED) society
is an international organization for facilitating the
sharing of microarray data from functional genomics
and proteomics experiments.
• MGED was established as a grass roots movement in
a meeting in November 1999 in Cambridge, UK
• Current tasks involve establishing standards for
microarray data annotation and representation,
facilitating the creation of microarray databases and
providing infrastructure for dissemination of
experimental and data transformation protocols
• Long term goals for the future will extend the mission to
other functional genomics and proteomics high
throughput technologies.
http://www.mged.org
An Experimental Ontology
• An ontology for microarray experiments
– Not an ontology of life but of experiments
– Parts are applicable to describing experiments in
general
• Our approach to interfacing with other ontologies
is “experimental”
– Not mapping terms from related ontologies
– Provide a framework to hang other ontologies off of
• Know where to find different types of annotation
• How to interpret that annotation
Microarray Information to be Captured
Figure from:
David J. Duggan et al. (1999) Expression Profiling using cDNA microarrays. Nature Genetics 21: 10-14
Flow Chart for Microarray Data
Minimal Information About a
Microarray Experiment (MIAME)
• Provides the concepts for the ontology
• Array design description
– Common features of the array as the whole, and the description of each
array design elements (e.g., each spot)
• Gene expression experiment description
–
–
–
–
Experimental design
Samples used, extract preparation and labeling
Hybridization procedures and parameters
Measurement data and specifications of data processing
• See Brazma et al Nature Genetics 2001 and
http://www.mged.org/Workgroups/MIAME/miame.html
MIAME Section on Samples (Biomaterials)
•
•
Biosource properties
– Organism
– Contact details for sample
– Descriptors relevant to the particular sample, such as
• Sex
• Age
• Developmental stage
• Organism part (tissue)
• Cell type
• Animal/ plant strain or line
• Genetic variation (e.g., gene knockout, transgenic variation)
• Individual genetic characteristics (e.g., disease alleles, polymorphisms)
• Disease state or nornal
• Is additional clinical information available (link)
• The individual (for interrelation of the samples in the experiment)
Biomaterial manipulations: laboratory protocol, including relevant parameters, e.g.,
– Growth conditions
– In vivo treatments (organism or individual treatments)
– In vitro treatments (cell culture conditions)
– Treatment type (e.g., small molecule, heat shock, cold shock, food deprivation)
– Compound
– Separation technique (e.g., none, trimming, microdissection, FACS)
MicroArray Gene Expression
Object Model (MAGE OM)
• Provides some specification of concepts
• Developed to provide an exchange format
for microarray data.
– Implemented in XML (MAGE-ML)
Relationship of MGED Efforts
MIAME
DB
MAGE
MGED Ontology
External
Ontologies/CVs
MIAME
DB
The MGED Ontology Working Group
• Acts through
– a mailing list of over 250
– working group meetings organized at conferences like
ISMB and of course MGED
• Collects resources (dictionaries, controlled
vocabularies, ontologies) for terms to describe
microarray experiments
– Sample (biomaterial)
– Experimental conditions (treatments)
– Experimental design (study design)
The MGED Ontology Home Page
http://www.cbil.upenn.edu/Ontology
The MGED Ontology Provides a Listing of Resources for Many Species
The MGED Ontology Organizes the Resources According to Concepts
The MGED Ontology is Structured in
DAML+OIL using OILed 3.4
MGED Ontology: BiomaterialDescription:
BiosourceProperty: Age
MGED Ontology: BiosourceOntologyEntry:
DiseaseState
MGED Ontology: Study
MGED Ontology Use Cases
• Make it easier and more accurate to annotate a microarray
experiment.
– Build forms that provide menus of terms and links to external resources.
See MIAMEexpress!
– Only ask for relevant terms and fill in terms that can be inferred.
• Use structured fields and controlled terms to query databases.
– Return a summary of all experiments that use a specified type of
biosource.
– Return a summary of all experiments done examining effects of a
specified treatment
• ? Aid in experiment design by providing parameters to consider
about samples, organization of treatments.
• ? Use to check if “MIAME-compliant.”
– Assess only fields that are relevant
– Check for proper use of terms
• ? Build gene networks based on biomaterial description
– Use structured descriptions to cluster, build models, etc.
MGED Ontology
©-BioMaterialDescription
External References
Instances
©-Biosource Property
©-Organism
NCBI Taxonomy
©-Age
Mus musculus musculus id: 39442
7 weeks after birth
©-DevelopmentStage
©-Sex
©-StrainOrLine
Mouse Anatomical Dictionary
International Committee on Standardized
Genetic Nomenclature for Mice
©-BiosourceProvider
©-OrganismPart
Stage 28
Female
C57BL/6N
Charles River, Japan
Mouse Anatomical Dictionary
Liver
©-BioMaterialManipulation
©-EnvironmentalHistory
©-CultureCondition
©-Temperature
22  2C
©-Humidity
55  5%
©-Light
12 hours light/dark cycle
©-PathogenTests
Specified pathogen free conditions
©-Water
ad libitum
©-Nutrients
MF, Oriental Yeast, Tokyo, Japan
©-Treatment
©-CompoundBasedTreatment
(Compound)
(Treatment_application)
(Measurement)
ChemIDplus
Fenofibrate, CAS 49562-28-9
in vivo, oral gavage
100mg/kg body weight
An example of microarray sample annotation using the MGED ontology
Susanna A. Sansone, Helen Parkinson, Philippe Rocca-Serra,
Chris Stoeckert and Alvis Brazma
The MGED Ontology in Action: MIAMExpress
The MGED Ontology in Action: RAD
Summary
• The MGED Ontology is being developed within
the microarray community to provide consistent
terminology for experiments.
• This community effort has resulted in a list of
multiple resources for many species.
• The list is organized by defined concepts and
augmented with terms for widely applicable
concepts (e.g., “age”, “sex”).
• The concepts are structured in DAML+OIL and
available in other formats (rdfs)
• The MGED Ontology is a work in progress
– More instances (create IDs)
– Constraints
– Concepts for other parts of microarray experiment
http://www.ebi.ac.uk/SOFG