Transcript Strategies for functional modeling

Strategies for functional
modeling
NMSU GO Workshop
20 May 2010
Types of data sets and modeling
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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.
Overview of Functional Modeling Strategy
Microarray Ids
ArrayIDer
Protein/Gene
identifiers
Pathways and
network analysis
GO Enrichment
analysis
GORetriever
Ingenuity Pathways Analysis (IPA)
Pathway Studio
Cytoscape
DAVID
Ingenuity Pathways Analysis (IPA)
Pathway Studio
Cytoscape
DAVID
EasyGO/AgriGO
Onto-Express
Onto-Express-to-go (OE2GO)
GO annotations
Genes/Proteins with
no GO annotations
GOanna
GOSlimViewer
Yellow boxes represent AgBase tools
Green/Purple boxes are non-AgBase resources
Functional Modeling Considerations
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Should I add my own GO?
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Should I do GO analysis and pathway analysis and
network analysis?
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use GOSlimViewer to see how much GO is available for your
species
use GORetriever to see how much GO is available for your
dataset
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?
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which tools have data for your species of interest?
what type of accessions are accepted?
availability (commercial and freely available)
Converting accessions
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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:
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DAVID
g:profiler
GORetriever
ArrayIDer – converts EST accessions
Converting accessions (cont’d)
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Commercial arrays
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EST arrays
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Commercial ID
mapping eg. NetAffy
Ensembl BioMart
Online tools
(g:convert, DAVID)
ArrayIDer
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Custom arrays
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Proteomics
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UniProt ID Conversion
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RNA-Seq data
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Working on your own data or examples:
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Your own data set
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New to GO
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retrieve existing GO (accession conversion?) &
group using slim sets
try functional grouping (DAVID, AgriGO, etc)
GO browser tutorials to familiarize yourself with
GO
work on some example data sets
Example data sets
Your own data
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Start by retrieving existing GO
(GORetriver)
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may need to do accession conversion
GOanna – for sequence data sets
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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.
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GO Browsers
search for gene products
 search for GO terms
 retrieve batch GO
 some analysis tools (slim sets, enrichment
analysis, etc)
 QuickGO at EBI
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http://www.ebi.ac.uk/QuickGO/
AmiGO at GO Consortium
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http://amigo.geneontology.org
Example Dataset 1
Chicken Affymetrix Array
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Converting Accessions
Retrieving GO annotations
Grouping using GOSlimViewer
GO term enrichment analysis using DAVID
GO term enrichment analysis using AgriGO
Example Dataset 2
EST Array and adding your own GO
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Converting Accessions
Retrieving GO annotations
Adding GO annotations
GO enrichment analysis using additional GO
annotations
Example Dataset 3
Modeling quantitative data
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GOModeler
agriGO
What other
information
should we add
to your
workshop
website??