Representing Flow Cytometry Experiments within FuGE Josef Spidlen 1, Peter Wilkinson 2, and Ryan...
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Transcript of Representing Flow Cytometry Experiments within FuGE Josef Spidlen 1, Peter Wilkinson 2, and Ryan...
Representing Flow Cytometry Experiments within FuGE
Josef Spidlen1, Peter Wilkinson2, and Ryan Brinkman1
1BC Cancer Research Centre, Vancouver, BC, Canada2University of Montreal, Montreal, QC, Canada
How can we accurately model “complex” flow cytometry
experiments in an exact manner?
FCS parameter(e.g., FL1)
Reagent
Reporter(e.g., PE)
Detector(e.g., Anti-CD4)
Cell population(e.g., CD4+)
Filter settings?
Emission spectra?
Compensation? ?
?
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
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
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
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
FuGE
Common
Bio
Description
Audit
Ontology
Protocol
Reference
Investigation
Data
Material
ConceptualMolecule
Common:• General data format management• Auditing• Referencing external resources• Protocols
Bio:• Investigation structure• Data• Materials (organisms, solutions, compounds)• Theoretical molecules e.g., sequences
FuGE structure
Using FuGE in practice
1. Extend UML with domain-specific components
• Encapsulate details in classes/attributes• Use “generic” classes with text-based
descriptions
2. Reference a FuGE entry for investigation structure and bio samples description
3. Define ontologies and use FuGE as it is for experimental metadata
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)
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
FuGE Protocol Types
1. Material treatment:Flow sample preparation
2. Data acquisition:Cytometer generates FCS
3. Data and material acquisition:Flow sorting
4. Data transformation:Compensation, gating, scaling, visualization
MaterialMaterial
DataMaterial
DataData
DataMaterial
Material
Flow Cytometry – DataFuGEFlow
Flow Cytometry – MaterialFuGEFlow
Flow Cytometry – ProtocolFuGEFlow
Computational ProtocolFuGEFlow
Computational ProtocolFuGEFlow
Computational ProtocolFuGEFlow
FuGEFlow
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
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.