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Workshop Aims

Workshop Aims. TAMU GO Workshop 17 May 2010. Aims of this Workshop. WIIFM? modeling examples background information about GO modeling Strategies for functional modeling of high throughput data sets (eg. arrays, proteomics, RNA-Seq) Continued support to help with modeling.

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Workshop Aims

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  1. Workshop Aims TAMU GO Workshop 17 May 2010

  2. Aims of this Workshop • WIIFM? • modeling examples • background information about GO modeling • Strategies for functional modeling of high throughput data sets (eg. arrays, proteomics, RNA-Seq) • Continued support to help with modeling

  3. http://www.agbase.msstate.edu/

  4. "Today’s challenge is to realise greater knowledge and understandingfrom the data-rich opportunities provided by modern high-throughput genomic technology."Professor Andrew Cossins, Consortium for Post-Genome Science, Chairman.

  5. What is the Gene Ontology? “a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing” the de facto standard for functional annotation assign functions to gene products at different levels, depending on how much is known about a gene product is used for a diverse range of species structured to be queried at different levels, eg: find all the chicken gene products in the genome that are involved in signal transduction zoom in on all the receptor tyrosine kinases human readable GO function has a digital tag to allow computational analysis of large datasets

  6. Who uses GO? http://www.ebi.ac.uk/GOA/users.html

  7. Functional Modeling Approaches • GO analysis • functional representation of gene products • need to add your own GO? • Pathway analysis • GO Biological Process includes some pathways, but may not be comprehensive • organism specific pathway information is limited • Network analysis • GO Molecular Function includes interaction data, but may not be comprehensive/hard to extract • interactions – key molecules • regulation of system

  8. Functional Modeling Considerations • Should I add my own GO? • use GOProfiler to see how much GO is available for your species • use GORetriever to see how much GO is available for your dataset • Should I do GO analysis and pathway analysis and network analysis? • different functional modeling methods show different aspects about your data (complementary) • is this type of data available for your species (or a close ortholog)? • What tools should I use? • which tools have data for your species of interest? • what type of accessions are accepted? • availability (commercial and freely available)

  9. Key Points • Modeling is subordinate to the biological questions/hypotheses. • Together the Gene Ontology and canonical genetic networks/pathways provide the central and complementary foundation for modeling functional genomics data. • Annotation follows information and information changes daily: STEP 1 in analyzing functional genomics data is re-annotating your dataset. • There is no “right answer”: different ways of looking at your data will give you different insights.

  10. Tools and materials from this workshop will be available online at the AgBase database Educational Resources link. • For continuing support and assistance please contact: agbase@cse.msstate.edu This workshop is supported by USDA CSREES grant number MISV-329140.

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