GO Enrichment analysis
description
Transcript of GO Enrichment analysis
GO Enrichment analysisCOST Functional Modeling Workshop22-24 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:21900207
PMID:15994189
PMID:20132535
http://www.geneontology.org
Determining which classes of gene products are
over-represented or under-represented.
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/
functional grouping – including GO, pathways, gene-disease association
ID Conversion search functionally related genes regular updates (*) online support & publications
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
http://bioinfo.cau.edu.cn/agriGO
Onto-Express
Onto-Express analysis instructions areAvailable in onto-express.ppt
http://vortex.cs.wayne.edu/projects.htm
Species represented in Onto-Express
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
• microarray analysis • "Batch-Genes analysis" allows analysis of HTP
data sets:
http://omicslab.genetics.ac.cn/GOEAST
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.