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Increasing GO Annotation Through Community Involvement

This presentation discusses the importance of community involvement in increasing Gene Ontology (GO) annotation, targeting annotations, and improving annotation quality scores.

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Increasing GO Annotation Through Community Involvement

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  1. Increasing GO Annotation Through Community Involvement Fiona McCarthy*, Nan Wang*, Susan Bridges** and Shane Burgess** http://www.agbase.msstate.edu/ GO Consortium User Meeting, 10 Sept 2006

  2. Who Are We? Dr Shane Burgess Dr Susan Bridges Divyaswetha Peddinti Nan Wang Bryce Magee Teresia Buza

  3. MGI: Judith Blake, David Hill, Mary Dolan GOA: Evelyn Camon, Dan Barrell GO Editorial Office: Jennifer Clark, Midori Harris dictyBase: Rex Chisholm, Eric Just GO Consortium Member mentor

  4. Overview • From genes to function • How much GO do I need? • Getting more GO annotation: targeted GO annotation and community involvement • Targeting GO annotations • GO annotation quality scores • communty directed annotation • Community annotation • The hook: what’s in it for me?

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

  6. From Genes to Function

  7. Use GO for……. • Grouping gene products by biological function • Determining which classes of gene products are over-represented or under-represented • Focusing on particular biological pathways and functions (hypothesis-driven data interrogation) • Relating a protein’s location to its function

  8. (PubMed 06/09/06) The number of publications using GO is increasing exponentially. Use of GO is increasing in species for which there is a dedicated GO annotation effort.

  9. How Much GO Do I Need? Compiled 15 June 06 using GOProfiler.

  10. How Much GO Do I Need? Compiled 15 June 06 using GOProfiler and PubMed.

  11. Analyzing Microrarray Data: • ‘breadth’ of annotation • how many gene products have GO annotation? • for each gene product, how many annotations? • ‘depth’ of annotation • how detailed is the GO annotation? • How can we effectively use our resources to get the best GO annotation?

  12. Getting more GO annotation • electronic GO annotations (IEA) • get many annotations quickly but lack detail (get ‘breadth’ but lack ‘depth’) • manual GO annotations • literature curation (gold standard) • Slower • many, many more researchers publishing papers than biocurators reading them • cleverer GO annotation: • targeted GO annotation • community involvement: researchers are the ‘local’ experts

  13. Targeting GO Annotation • target gene products with poor GO annotation • determining GO annotation quality • target gene products most interesting for the community • community feedback & prioritization

  14. GO Annotation Quality (GAQ) For a single gene product: GAQ = no. annotations x dag depth x evidence code • calculate overall GAQ score for an organism • calculate GAQ for functional subsets of gene products • target GO annotation efforts to genes in functional subsets with low GAQ score

  15. Comparative GAQ: Scores for Chicken and Mouse

  16. Comparative GAQ: Scores for Chicken Cell Processes

  17. Community Directed Annotation • AgBase web form to enable community requests • prioritization: • requests prioritized for each species • one gene product request equals one count • gene products with the most counts have higher priority • annotation time for each species is split proportionally based on the number of requests for each species • requests annotated using both ISS and available published literature • higher priority for gene products submitted to the community gene association file • priority for gene products commonly represented on arrays • prioritization modified based on community input

  18. Community Annotation • login allows annotations to be acknowledged and notification when the request is completed • users may request annotation of a gene product/PubMed reference • submitters assist in pertinant literature slection for curation • allows annotators to focus on GO annotations most important for the community • submitters notified when the request is completed • advanced submission allows trained users to upload gene association files for inclusion in the Community annotation file • quality checks before annotations are transferred from the Community file to the GOC file

  19. Targeting GO Annotation • use GAQ to target poorly annotated processes • determining GO annotation quality • use community requests to prioritize annotations BUT still many, many more researchers publishing papers than biocurators reading them… …and researchers need their data analyzed yesterday...

  20. Community GO Annotation AgBase provides 2 annotation files: • “GO Consortium” file: fully quality checked annotations that meet current GO Consortium guidelines • “Community” file: • annotations for ‘predicted proteins’ without UniProtKB identifiers (until 10 July 2006, were not supported by EBI-GOA) • ISS annotations to evidence codes no longer accepted (as of April 2006) • annotations from community researchers that have not been fully quality checked by a trained GO curator • these annotations will eventually be transferred to the GOC file or (for ISS) superseded by higher quality literature annotations

  21. AgBase Annotation Files GOC file = 1,508 GO associations Community file = 5,146 GO associations

  22. What’s in it for ME? • two tier annotation file systems provides most comprehensive annotation in instances where there are few annotations available • researchers can choose which annotation files best suits their system • researchers with GO training may submit (& be acknowledged for) their own annotations • researchers with specific knowledge of particular gene products can add to the annotation of their gene products of interest via the AgBase request page

  23. What’s in it for ME?

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