GO Enrichment analysis

1. GO Enrichment analysis COST Functional Modeling Workshop 22-24 April, Helsinki

2. Enrichment Analysis • Statistically compare a gene set (e.g., differentially expressed) to a background. • genomics, proteomics – all annotations for a species • microarrays – all annotations for array gene set • Different statistical tests • hypergeometric; binomial;, χ2 (chi-square); ; Fisher's exact test • RNASeq data analysis • effects of tissue-specific gene length biases

3. PMID:15994189 PMID:21900207 PMID:20132535

4. Determining which classes of gene products are over-represented or under-represented. http://www.geneontology.org

5. However…. • many of these tools do not support agricultural species • the tools have different computing requirements A list of these tools that can be used for agricultural species is available on the workshop website at the “Summary of Tools for gene expression analysis” link.

6. Evaluating GO tools Some criteria for evaluating GO Tools: • Does it include my species of interest (or do I have to “humanize” my list)? • What does it require to set up (computer usage/online) • What was the source for the GO (primary or secondary) and when was it last updated? • Does it report the GO evidence codes (and is IEA included)? • Does it report which of my gene products has no GO? • Does it report both over/under represented GO groups and how does it evaluate this? • Does it allow me to add my own GO annotations? • Does it represent my results in a way that facilitates discovery?

7. Some useful expression analysis tools: • Database for Annotation, Visualization and Integrated Discovery (DAVID) • http://david.abcc.ncifcrf.gov/ • AgriGO -- GO Analysis Toolkit and Database for Agricultural Community • http://bioinfo.cau.edu.cn/agriGO/ • used to be EasyGO • chicken, cow, pig, mouse, cereals, dicots • includes Plant Ontology (PO) analysis • Onto-Express • http://vortex.cs.wayne.edu/projects.htm#Onto-Express • can provide your own gene association file • Funcassociate 2.0: The Gene Set Functionator • http://llama.med.harvard.edu/funcassociate/ • can provide your own gene association file • Ontologizer • http://compbio.charite.de/contao/index.php/ontologizer2.html • Java based; allows you to upload your own files

9. http://david.abcc.ncifcrf.gov/ • functional grouping – including GO, pathways, gene-disease association • ID Conversion • search functionally related genes • regular updates (*) • online support & publications

11. http://bioinfo.cau.edu.cn/agriGO

12. http://bioinfo.cau.edu.cn/agriGO • enrichment analysis using either GO or Plant Ontology (PO) • > 40 species: chicken, cow, pig, mouse, cereals, poplar, fruits • new species added by request • GenBank, EMBL, UniProt • Affymetrix, Operon, Agilent arrays

13. Onto-Express http://vortex.cs.wayne.edu/projects.htm Onto-Express analysis instructions are Available in onto-express.ppt

14. Species represented in Onto-Express

15. Can upload your own annotations using OE2GO

16. http://llama.med.harvard.edu/funcassociate/

17. http://compbio.charite.de/contao/index.php/ontologizer2.html

18. http://omicslab.genetics.ac.cn/GOEAST

19. http://omicslab.genetics.ac.cn/GOEAST • microarray analysis • "Batch-Genes analysis" allows analysis of HTP data sets:

21. http://revigo.irb.hr

23. What next? Exercises or working on your own data sets: • Working on your own data set • continue with adding GO • decide what enrichment tool to use for you own data set (what species the tools accept, if the tools allow you to upload you own annotation file, etc) • Tutorial 4: GO Enrichment analysis • Use tutorial to try different enrichment tools – compare, determine which will work for you data set.