GO Enrichment analysis
COST Functional Modeling Workshop
22-24 April, Helsinki
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
PMID:15994189
PMID:21900207
PMID:20132535
Determining which classes of gene products are
over-represented or under-represented.
http://www.geneontology.org
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.
Evaluating GO tools
Some criteria for evaluating GO Tools:
1. Does it include my species of interest (or do I have to
“humanize” my list)?
2. What does it require to set up (computer usage/online)
3. What was the source for the GO (primary or secondary) and
when was it last updated?
4. Does it report the GO evidence codes (and is IEA included)?
5. Does it report which of my gene products has no GO?
6. Does it report both over/under represented GO groups and
how does it evaluate this?
7. Does it allow me to add my own GO annotations?
8. Does it represent my results in a way that facilitates discovery?
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
http://david.abcc.ncifcrf.gov/
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functional grouping – including GO, pathways, genedisease association
ID Conversion
search functionally related genes
regular updates (*)
online support & publications
http://bioinfo.cau.edu.cn/agriGO
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
Onto-Express
http://vortex.cs.wayne.edu/projects.htm
Onto-Express analysis instructions are
Available in onto-express.ppt
Species
represented
in OntoExpress
Can upload your
own annotations
using OE2GO
http://llama.med.harvard.edu/funcassociate/
http://compbio.charite.de/contao/index.php/ontologizer2.html
http://omicslab.genetics.ac.cn/GOEAST
http://omicslab.genetics.ac.cn/GOEAST
• microarray analysis
• "Batch-Genes analysis" allows analysis of HTP
data sets:
http://revigo.irb.hr
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.