The MGED Ontology: Providing Descriptors for Microarray Data Trish Whetzel Department of Genetics Center for Bioinformatics University of Pennsylvania

CBIL –Chris Stoeckert –Angel Pizarro –Elisabetta Manduchi EBI –Helen Parkinson –Susanna Sansone TIGR –Joe White Stanford –Cathy Ball Acknowledgements NCICB –Gilberto Fragoso –Liju Fan –Mervi Heiskanen Others –Paul Spellman –John Matese –Helen Causton Ontology Mailing List

MGED Society International organization Comprised of biologists computer scientists, and data analysts Aims to facilitate the sharing of functional genomics data generated by microarray and proteomics experiments –Establish standards for microarray data annotation –Create microarray databases –Promote sharing of high quality, well-annotated data

MGED Standardization Efforts MIAME –The formulation of the minimum information required about a microarray experiment in order to interpret and verify the results. MAGE –The establishment of a data exchange format (MAGE-ML) and an object model (MAGE-OM) for microarray experiments. Ontololgy Working Group –The development of an ontology to describe microarray experiments and in particular the biological material (biomaterial) used in these experiments. Transformations –The development of recommendations regarding microarray data transformations and normalization methods.

Microarray Information to be Shared Figure from: David J. Duggan et al. (1999) Expression Profiling using cDNA microarrays. Nature Genetics 21: 10-14

MGED Ontology (MO) Purpose –Provide standard terms for the annotation of microarray experiments Benefits –Unambiguous description of how the experiment was performed –Structured queries can be generated MGED Ontology concepts derived from the MIAME guidelines/MAGE-OM

MGED Ontology development Oiled File formats –Html file –Daml file –NCI DTS Browser

MGED Ontology Class Hierarchy MGED CoreOntology –In synch with MAGE v.1 –Stable class structure MGED ExtendedOntology –Classes for additional terms as the usage of MO expands for genomics technologies

Relationship of MO to MAGE-OM MO class hierarchy follows that of MAGE-OM –Association to OntologyEntry MO provides terms for these associations by: –Instances internal to MO –Instances from external ontologies Take advantage of existing ontologies

Relationship of MO and MAGE-OM

MO and References to External Ontologies

Desirable Microarray Queries Return all experiments with species X examined at developmental stage Y –Sort by platform type –Which are untreated? Treated? Treated with what compound? How comparable are these results? These questions can be asked of all experiments annotated using the MGED Ontology.

MO and Structured Queries

Future Work Convert to OWL –W3C standard ontology language –Expressivity Add terms to describe –Data transformation and normalization methods –Protocol types used by the Protein Data Bank

Future Work cont. Expand the MGED Extended Ontology by adding classes and terms to describe new domains and technologies –Toxicogenomics, ecotoxicogenomics and pharmacogenomics … A public forum for developing internationally compatible and public infrastructure for reporting array-based toxicogenomics. –Protein Standards Initiative Defines community standards for data representation in proteomics to facilitate data comparision, exchange and verification.

Links mged.org ontology.php

The Computational View of Microarray Information Need an ontology to unambiguously represent this information.

Issues to Discuss Burning Issues –Developing MO in synch with related efforts (MAGE-OM v.2.0) –Use/presentation in annotation forms –Coverage of other technologies and biological domains Flame retardant structure –ExtendedOntology Space to add new classes, terms and their relationship to one another

Relationship of MO and MAGE-OM

Microarray Information to be Shared

Experiment Sample RNA Extract Labeled nucleic acid Protocols Hybridizations Genes Array Design Microarray Gene expression data matrix normalization integration