1. Modeling Functional Genomics Datasets CVM8890-101 Lesson 3 13 June 2007Fiona McCarthy

2. Lesson 3: Tools for functional annotation. Accessing functional data; computational strategies to obtain more complete functional annotation; the AgBase GO annotation pipeline.

3. Lesson 3 Outline 1.Review: Functional Annotation 2.Tools for functional annotation –Accessing functional data –Computational strategies to obtain more functional data 3.Example: The AgBase GO annotation pipeline 4.Other GO annotation tools

4. Review: Functional Annotation biologists refer to both the annotation of the genome and functional annotation of gene products: “structural” AND “functional” annotation Functional annotation is required to make biological sense of high throughput datasets eg. genomics, arrays, proteomics COGs, KOGs, GO

5. Tools for Functional Annotation Need to be able to access functional annotation for your dataset –Breadth and depth –Date updated –No annotation vs function unknown Need to be able to add more annotation Need to be able to use the annotations to model your data –Depth or detail –Compatibility with other programs (eg pathway analysis) –Comparative data?

6. Tools for Functional Annotation Clusters of Orthologous Groups (COGs) euKaryotic Orthologous Groups (KOGs) UniProt Knowledgebase (UniProtKB) Bioinformatic Harvester FANTOM Puma Gene Ontology (GO)

7. COGs & KOGs Accessible at http://www.ncbi.nlm.nih.gov/COG/ ftp download Available for many prokaryotes and 7 eukaryotes Add more annotation using the KOGinator? Modeling: –Has breadth but not always depth –Good for prokaryote comparative analysis?

8. COGs & KOGs

9. http://www.ncbi.nlm.nih.gov/COG/ Automated tools for large numbers of comparisons??

10. UniProtKB Accessible at http://www.pir.uniprot.org/ ftp download & sophisticated search & download capabilities Available for > 132,000 species Annotation across both literature (for selected species) and biological databases Modeling: –Has breadth but not always depth; many proteins not represented in UniProtKB –Those that are represented have a detailed summary of function from a range of sources –Rapid help and feedback from the database help

11. UniProtKB http://www.pir.uniprot.org/

12. UniProtKB http://www.pir.uniprot.org/

13. UniProtKB http://www.pir.uniprot.org/

14. Bioinformatic Harvester Accessible at http://harvester.fzk.de/harvester/ no download Available for 6 model species Integrates data from multiple sources Modeling: –Has breadth and depth; not useful for large datasets –Updates?

15. Bioinformatic Harvester http://harvester.fzk.de/harvester/

16. FANTOM http://www.gsc.riken.go.jp/e/FANTOM/ Mouse only

17. PUMA http://compbio.mcs.anl.gov/puma2/

18. Gene Ontology Accessible at http://www.geneontology.org/ updated downloads for 34 species + downloads for UniProtKB species (>130,000) UniProtKB species annotation: some depth, less breadth GO data mapped from other databases Modeling: –Many tools available for modeling using the GO –Can use computational or manual curation to add annotations

19. Gene Ontology http://www.geneontology.org/

20. Accessing GO Data

21. EBI-GOA Project http://www.ebi.ac.uk/GOA/

22. The AgBase GO Annotation Pipeline Accessible at http://www.agbase.msstate.edu/ Access available annotations for agriculturally important species Provide your own GO annotations Model GO for your dataset

23. Coming soon; GOModeler quantitative hypothesis driven modeling using GO

25. http://www.geneontology.org/GO.tools.shtml Other GO Annotation Tools

26. Evaluate: Can I run it from my computer? Does it include my species of interest? When was it last updated? Does it display evidence codes? Does it display IEA annotations? What are the inputs it accepts? Does it do batch searches? Other GO Annotation Tools

27. Using GO to Analyze Array Data

28. Evaluate: Does it include my species of interest? When were the annotations last updated? Can I add my own annotations? Does it tell me how many of my genes are used for the analysis? Does it account for “not” annotations? Does it display IEA annotations? What are the input IDS it accepts? Does it analyze both over & under-represented terms? What statistics does it use for the analysis? Does it do a graphical representation? ANY tool will only be as good as the annotations.