GO Enrichment analysis

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

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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 - PowerPoint PPT Presentation

Transcript of GO Enrichment analysis

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GO Enrichment analysisCOST Functional Modeling Workshop22-24 April, Helsinki

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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

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PMID:21900207

PMID:15994189

PMID:20132535

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http://www.geneontology.org

Determining which classes of gene products are

over-represented or under-represented.

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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.

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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?

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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

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http://david.abcc.ncifcrf.gov/

functional grouping – including GO, pathways, gene-disease association

ID Conversion search functionally related genes regular updates (*) online support & publications

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

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• 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

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Onto-Express

Onto-Express analysis instructions areAvailable in onto-express.ppt

http://vortex.cs.wayne.edu/projects.htm

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Species represented in Onto-Express

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Can upload your own annotations

using OE2GO

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

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

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

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• microarray analysis • "Batch-Genes analysis" allows analysis of HTP

data sets:

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

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http://revigo.irb.hr

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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.