Strategies for functional modeling

1. Strategies for functional modeling TAMU GO Workshop 17 May 2010

2. Types of data sets and modeling • Commercial array data – more likely to have ID mapping to support functional modeling. • Custom/USDA array data – may need to do your own ID mapping: see examples on workshop page. • Proteomics data • RNA-Seq data sets – computational pipelines to assign GO (GOanna is limited; contact AgBase). • Real-time data or quantitative proteomics data – hypothesis testing.

4. Overview of Functional Modeling Strategy Microarray Ids Pathways and network analysis Ingenuity Pathways Analysis (IPA) Pathway Studio Cytoscape DAVID ArrayIDer Protein/Gene identifiers GO Enrichment analysis Ingenuity Pathways Analysis (IPA) Pathway Studio Cytoscape DAVID EasyGO/AgriGO Onto-Express Onto-Express-to-go (OE2GO) GORetriever GO annotations Genes/Proteins with no GO annotations GOSlimViewer Yellow boxes represent AgBase tools Green/Purple boxes are non-AgBase resources GOanna

5. Functional Modeling Considerations • Should I add my own GO? • use GOSlimViewer 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)

6. Converting accessions • Depending on your data set & the tools you use, you are likely to need to convert between database accessions to do your functional modeling. • UniProt database – ID mapping tab • Ensembl BioMart • Online analysis tools: • DAVID • g:profiler • GORetriever • ArrayIDer – converts EST accessions

7. Commercial arrays Custom arrays EST arrays Proteomics RNA-Seq data Commercial ID mapping eg. NetAffy Ensembl BioMart Online tools (g:convert, DAVID) ArrayIDer UniProt ID Conversion Converting accessions (cont’d)

8. Working on your own data or examples: • Your own data set • retrieve existing GO (accession conversion?) & group using slim sets • try functional grouping (DAVID, AgriGO, etc) • New to GO • GO browser tutorials to familiarize yourself with GO • work on some example data sets • Example data sets

9. Your own data • Start by retrieving existing GO (GORetriver) • may need to do accession conversion • GOanna – for sequence data sets • If you haven’t had results returned from GOanna, sample results are available in the example data sets • Try functional analysis using DAVID, AgriGO or etc • For help with hypothesis modeling etc, see me.

10. GO Browsers • search for gene products • search for GO terms • retrieve batch GO • some analysis tools (slim sets, enrichment analysis, etc) • QuickGO at EBI • http://www.ebi.ac.uk/QuickGO/ • AmiGO at GO Consortium • http://amigo.geneontology.org

12. Example Dataset 1 Chicken Affymetrix Array • Converting Accessions • Retrieving GO annotations • Grouping using GOSlimViewer • GO term enrichment analysis using DAVID • GO term enrichment analysis using AgriGO

13. Example Dataset 2 EST Array and adding your own GO • Converting Accessions • Retrieving GO annotations • Adding GO annotations • GO enrichment analysis using additional GO annotations

14. Example Dataset 3 Modeling quantitative data 1. GOModeler 2. agriGO

15. What other information should we add to your workshop website??