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The European Bioinformatics Institute MIAME and Ontologies for Sample Description Helen Parkinson Microarray Informatics Team European Bioinformatics Institute.

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Presentation on theme: "The European Bioinformatics Institute MIAME and Ontologies for Sample Description Helen Parkinson Microarray Informatics Team European Bioinformatics Institute."— Presentation transcript:

1 The European Bioinformatics Institute MIAME and Ontologies for Sample Description Helen Parkinson Microarray Informatics Team European Bioinformatics Institute EMBO Course, October 2001

2 The European Bioinformatics Institute Talk Structure  ArrayExpress - a public database for microarray data and integration of ontologies  Ontologies for gene expression data  Submission and annotation tool

3 The European Bioinformatics Institute Problems of microarray data analysis  Size of the datasets  Different platforms - nylon, glass  Different technologies on platforms- oligo/spotted  Referencing external databases which are not stable  Sample annotation  Array annotation  Need for LIMS systems and the need for bioinformaticians

4 The European Bioinformatics Institute General MIAME principles  Recorded info should be sufficient to interpret and replicate the experiment  Information should be structured so that querying and automated data analysis and mining are feasible

5 The European Bioinformatics Institute A gene expression database from the data analyst’s point of view Samples Genes Gene expression levels Sample annotations Gene annotations Gene expression matrix

6 The European Bioinformatics Institute Gene Annotation  Can be given by links to gene sequence databases and GO can be used on the analysis side ( function,process,cell compartment )  MIAME is flexible, allows many kinds of sequence identifiers or even sequence itself.  In some cases it’s more useful to include a real sequence than an inaccurate id  In the end we will need a mapping from a gene list to all the spots on all arrays, this is non trivial given the problems with names

7 The European Bioinformatics Institute Sample annotation  Gene expression data only have meaning in the context of detailed sample descriptions  If the data is going to be interpreted by independent parties, sample information has to be searchable and in the database  Controlled vocabularies and ontologies (species, cell types, compound nomenclature, treatments, etc) are needed for unambiguous sample description

8 The European Bioinformatics Institute Standardisation of microarray data and annotations -MGED group The goal of the group is to facilitate the adoption of standards for DNA-array experiment annotation and data representation, as well as the introduction of standard experimental controls and data normalisation methods. Includes most of the worlds largest microarray laboratories and companies (TIGR,Affymetrix Stanford,Sanger,Agilent etc) www.mged.org

9 The European Bioinformatics Institute Sample annotation- what can be done?  Build an ontology for gene expression data (MGED)  Use existing ontologies and link them in  Incorporate the ontology into the database  Develop internal editing tools for the ontology  Develop browser or other interface for the ontology and link to LIMS  Some use of free text descriptions are unavoidable (curation workload)

10 The European Bioinformatics Institute Use case scenarios  Return a summary of all experiments that use a specified type of biosource (primary source).  Group the experiments according to treatment.  Return a summary of all experiments done examining effects of a specified treatment  Group the experiments according to biosource.  Return a summary of all experiments measuring the expression of a specified gene.  Indicate when experiments confirm results, provide new information, or conflict.

11 The European Bioinformatics Institute MIAME – Minimum Information About a Microarray Experiment Publication External links 6 parts of a microarray experiment www.mged.org HybridisationArray Gene (e.g., EMBL ) Sample Source (e.g., Taxonomy ) Data Experiment Normalisation

12 The European Bioinformatics Institute MGED Biomaterial (sample) Ontology  Under construction by Chris Stoeckert – Using OILed (though other tools exist)  Motivated by MIAME and coordinated with the database model  We will extend classes, provide constraints, define terms, provide new terms and develop cv’s for submissions (EBI)

13 The European Bioinformatics Institute Part of the MGED biomaterial ontology class Age documentation: The time period elapsed since an identifiable point in the life cycle of an organism. If a developmental stage is specified, the identifiable point would be the beginning of that stage. Otherwise the identifiable point must be specified such as planting. type: primitive superclasses: BiosourceProperty constraints: slot-constraint has_measurement has-value Measurementslot- constraint initial_time_point has-value one-of (planting beginning_of_stage) used in slots: initial_time_point

14 The European Bioinformatics Institute organism (NCBI taxonomy) cell source - provider cell type (if derived from primary sources (s)) sex age growth conditions development stage organism part (tissue) animal/plant strain or line genetic variation (e.g., gene knockout, transgenic variation) individual individual genetic characteristics (e.g., disease alleles, polymorphisms) disease state or normal target cell type cell line and source (if applicable) 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 is additional clinical information available (link) separation technique (e.g., none, trimming, microdissection, FACS) laboratory protocol for sample treatment…… MIAME Section on Sample Source and Treatment

15 The European Bioinformatics Institute Examples of usable external ontologies  NCBI taxonomy database  Jackson Lab mouse strains and genes  Edinburgh mouse atlas anatomy  HUGO nomenclature for Human genes  Chemical and compound Ontologies - Merck index  TAIR  Flybase  GO

16 The European Bioinformatics Institute Excerpts from a Sample Description courtesy of M. Hoffman, S. Schmidtke, Lion BioSciences Organism: Mus musculus [ NCBI taxonomy browser ] Cell source: in-house bred mice (contact: person@somewhere.ac.uk) Sex: female [ MGED ] Age: 3 - 4 weeks after birth [ MGED ] Growth conditions: normal controlled environment 20 - 22 o C average temperature housed in cages according to EU legislation specified pathogen free conditions (SPF) 14 hours light cycle 10 hours dark cycle [Developmental stage]: stage 28 (juvenile (young) mice)) [ GXD "Mouse Anatomical Dictionary" ] Organism part: thymus [ GXD "Mouse Anatomical Dictionary" ] Strain or line: C57BL/6 [International Committee on Standardized Genetic Nomenclature for Mice] Genetic Variation: Inbr (J) 150. Origin: substrains 6 and 10 were separated prior to 1937. This substrain is now probably the most widely used of all inbred strains. Substrain 6 and 10 differ at the H9, Igh2 and Lv loci. Maint. by J,N, Ola. [International Committee on Standardized Genetic Nomenclature for Mice ] Treatment: in vivo [MGED] [intraperitoneal] injection of [Dexamethasone] into mice, 10 microgram per 25 g bodyweight of the mouse Compound: drug [MGED] synthetic [glucocorticoid] [dexamethasone], dissolved in PBS

17 The European Bioinformatics Institute Introduction to the database  ArrayExpress is implemented in Oracle  The submission tool is a different implementation of the ArrayExpress model in Mysql  Faster, easier to update  Short term solution to the problem of data submission

18 The European Bioinformatics Institute ArrayExpress conceptual model Publication External links HybridisationArraySample Source (e.g., Taxonomy ) Experiment Normalisation Gene (e.g., EMBL ) Data

19 The European Bioinformatics Institute ArrayExpress Database MAGE-OM Model Curation Database User Login Array Submission Protocol Sub. Experiment submission Submission tool Query Interface for Public Data Analysis Tools Expression Profiler Large Scale Submissions MAGE-ML format Submitter LIMS Browse Arrays Browse Protocols Data File Export External Applications Browse Arrays External Databases, EMBL, Ontology Resources… etc

20 The European Bioinformatics Institute MIAMExpress  Based on MIAME concepts and questionnaire  Experiment, Array, Protocol submissions  CV/Ontology wherever possible  Future versions organism specific pages and related linked ontologies  Allow user driven ontology development  Will be developed according to user needs  Will also need to be an update tool

21 The European Bioinformatics Institute Design Considerations  Speed and ease of use, scalability  Need to browse existing protocols and array designs in ArrayExpress  Requirement for curator control over submissions  Submissions tracking  Future use as a LIMS  Flexibility

22 The European Bioinformatics Institute Features of MIAMExpress  Creates a user login account instead of on- the-fly submissions so sessions can be saved  Allows existing protocols to be copied and saved and linked to more than one hyb/expt  Forms the basis of a LIMS using the ArrayExpress model  Will be available as a stand alone tool for local installation  Is open source and free  Will be supported by curation staff and developers

23 The European Bioinformatics Institute

24 Expected Users  Users with limited local bioinformatics support  Users of bought in arrays without LIMS  Small scale users with self made arrays who will need to provide a description  Commercial arrays descriptions will be provided

25 The European Bioinformatics Institute Acknowledgments  Whole Microarray Informatics Team, EBI, esp. Alvis Brazma, Mohammad Shojatalab and Ugis Sarkans  Industry Support team, EBI  MGED steering committee  MIAME working group  Chris Stoeckert, U. Penn. and members of MGED

26 The European Bioinformatics Institute Demo Version of MIAMExpress  Coming soon to www.ebi.ac.uk.microarray www.ebi.ac.uk.microarray  Beta tester recuitment


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