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Representing Flow Cytometry Experiments within FuGE

Representing Flow Cytometry Experiments within FuGE. Josef Spidlen 1 , Peter Wilkinson 2 , and Ryan Brinkman 1 1 BC Cancer Research Centre, Vancouver, BC, Canada 2 University of Montreal, Montreal, QC, Canada. Reagent. Reporter (e.g., PE). Detector (e.g., Anti-CD4).

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Representing Flow Cytometry Experiments within FuGE

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  1. Representing Flow Cytometry Experiments within FuGE Josef Spidlen1, Peter Wilkinson2, and Ryan Brinkman1 1BC Cancer Research Centre, Vancouver, BC, Canada 2University of Montreal, Montreal, QC, Canada

  2. Reagent Reporter (e.g., PE) Detector (e.g., Anti-CD4) How can we accurately model “complex” flow cytometry experiments in an exact manner? FCS parameter (e.g., FL1) Cell population (e.g., CD4+) ? Filter settings? ? Compensation? Emission spectra?

  3. Why would we even want to? • Sharing experimental details • Understanding third party experiments • Collaboration • Independent validation • Common and sharable software tools • High-throughput data processing • New data processing methods

  4. FuGE • Functional Genomics Experiment Object Model • A model of the common components of functional genomics experiments • FuGE is developed by members of MGED/PSI with input from ‘cross-omics’ experimentalists • Aims to help the development of data standards • Should allow some cross-compatibility between different ‘omics’ experiments

  5. What is FuGE? • An object model in UML • An XML Schema (generated from UML) • A software API (created from UML) • ER schema (generated from UML) • Milestone 3 UML2 - August 2006 • Current state: Version 1.0 candidate

  6. Benefits of shared model components • Queries over common annotation • Samples, hypotheses, protocols • Shared software for experimental annotation and analysis • Reduced development and learning times through the sharing of consistent practice • Eased integrating of functional genomics data • Developing standards for each technique is a hard problem • Shared resources could alleviate problems

  7. FuGE structure Audit • Common: • General data format management • Auditing • Referencing external resources • Protocols Description Ontology Protocol Common Reference FuGE • Bio: • Investigation structure • Data • Materials (organisms, solutions, compounds) • Theoretical molecules e.g., sequences Data Bio Investigation Material Conceptual Molecule

  8. Using FuGE in practice • Extend UML with domain-specific components • Encapsulate details in classes/attributes • Use “generic” classes with text-based descriptions • Reference a FuGE entry for investigation structure and bio samples description • Define ontologies and use FuGE as it is for experimental metadata

  9. FuGE extensions • MAGE V2 • Format for microarray data and annotations • GelML • Gel electrophoresis, format for methods and results • spML • Sample processing: liquid chromatography, capillary electrophoresis, … • CPAS • Computational Proteomics Analysis System – set of bioinformatics tools to help scientists store, analyze, and share data from experiments and clinical trials • PRIDE • Proteomics Identification Database contemplating FuGE for data format • Metabolomics community – considering • MIACA (Minimum Information About a Cellular Assay) – considering • Flow Cytometry • FuGE was chosen as core for flow cytometry object model during FICCS OMWG Development Workshop (Dallas, October 2006)

  10. FuGE – Main Abstract Classes • Everything is “Describable” • Text based description • Ontology reference • Custom properties (keyword / value pairs) • Most classes are “Identifiable” • “Identifiable” is “Describable” • Unique identifier • Name, database references

  11. Material Material Material Data Data Material Material Data Data FuGE Protocol Types • Material treatment: Flow sample preparation • Data acquisition: Cytometer generates FCS • Data and material acquisition: Flow sorting • Data transformation: Compensation, gating, scaling, visualization

  12. FuGE Flow Flow Cytometry – Data

  13. FuGE Flow Flow Cytometry – Material

  14. FuGE Flow Flow Cytometry – Protocol

  15. FuGE Flow Computational Protocol

  16. FuGE Flow Computational Protocol

  17. FuGE Flow Computational Protocol

  18. FuGE Flow

  19. Conclusions • Initial work on extending FuGE has been done • Can be downloaded using subversion from https://svn.sourceforge.net/svnroot/flowcyt/ • Pretty high level so far • Need to incorporate more details • Need to validate the model • Encoding various use cases • An iterative approach needed

  20. Acknowledgement • Members of the FICCS OMWG • Keith Boyce, Ryan Brinkman, Jennifer Cai, Mark Dalphin, Megan Kong, Jamie Lee, Yu (Max) Qian, Richard Scheuermann, Peter Wilkinson, and others. • Introduction to FuGE based on original presentations from FuGE development team • Angel Pizarro, Andrew Jones, Paul Spellman, Michael Miller, and others.

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