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GO-based tools for functional modeling GO Workshop 3-6 August 2010

GO-based tools for functional modeling

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GO-based tools for functional modeling. GO Workshop 3-6 August 2010. Functional Modeling. Grouping by function GO Slim sets GO browser tools GOSlimViewer GO enrichment analysis DAVID EasyGO/agriGO Onto-Express Funcassociate 2.0 Pathway & network analysis Hypothesis testing. - PowerPoint PPT Presentation

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Page 1: GO-based tools for functional modeling

GO-based tools for functional

modeling

GO Workshop3-6 August 2010

Page 2: GO-based tools for functional modeling

Functional Modeling Grouping by function

GO Slim sets GO browser tools GOSlimViewer

GO enrichment analysis DAVID EasyGO/agriGO Onto-Express Funcassociate 2.0

Pathway & network analysis Hypothesis testing

Page 3: GO-based tools for functional modeling

Grouping by function

Page 4: GO-based tools for functional modeling

GO Slim Sets slim sets are abbreviated versions of the GO contain broader functional terms made by different GO Consortium groups (for different

purposes, eg. plant, yeast, etc) need to cite which one you used!

More information about GO terms for each slim set can be found at EBI QuickGO:http://www.ebi.ac.uk/QuickGO/

GO Slim and Subset Guide http://www.geneontology.org/GO.slims.shtml

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QuickGO: Create your own subset/slim of GO terms http://www.ebi.ac.uk/QuickGO/ GO slims tutorial available This tutorial will describe GO slims, what they are

used for and how to use QuickGO for: * creating a custom GO slim * using a pre-defined GO slim * obtaining GO annotations to a GO slim * customising a set of slimmed annotations * using statistics calculated by QuickGO to

generate graphical representations of the data

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AmiGO: GO Slimmer http://amigo.geneontology.org/cgi-bin/ami

go/slimmer?session_id=4878amigo1273279396

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GOSlimViewer input file

Input is a text file containing 3 tab separated columns:

1. accession

2. GO:ID

3. aspect (P,F or C)

• file provided by GORetriever and GOanna2ga

• can manually add to it from GOanna excel file

allows you to include your additional GO annotations in the analysis

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GOSlimViewer output

Page 10: GO-based tools for functional modeling

GOSlimViewer output

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GOSlimViewer output

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GO Enrichment analysis

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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 toolsSome 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?

Page 17: GO-based tools for functional modeling

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

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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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May 2010: EasyGO replaced by agriGO

http://bioinformatics.cau.edu.cn/easygo/

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enrichment analysis using either GO or Plant Ontology (PO)

40 species: chicken, cow, pig, mouse, cereals, poplar, fruits

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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Pathway & network analysis

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GO, Pathway, Network Analysis Many GO analysis tools also include

pathway & network analysis Ingenuity Pathways Analysis (IPA) and

Pathway Studios – commercial software DAVID – includes multiple functional

categories Onto-Tools – includes Pathways Express

tool

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Pathways & Networks

A network is a collection of interactions

Pathways are a subset of networks Network of interacting proteins that carry out biological

functions such as metabolism and signal transduction

All pathways are networks of interactions

Not all networks are pathways

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KEGG http://www.genome.jp/kegg/pathway.html/BioCyc http://www.biocyc.org/Reactome http://www.reactome.org/GenMAPP http://www.genmapp.org/BioCarta http://www.biocarta.com/

Pathguide – the pathway resource list http://www.pathguide.org/

Pathways Resources

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Page 31: GO-based tools for functional modeling

Biological Networks

Networks often represented as graphs Nodes represent proteins or genes that

code for proteins Edges represent the functional links

between nodes (ex regulation) Small changes in graph’s

topology/architecture can result in the emergence of novel properties

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Types of interactions protein (enzyme) – metabolite (ligand)

metabolic pathways

protein – protein cell signaling pathways, protein complexes

protein – gene genetic networks

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Sod1 Mus musculus

Network example: STRING Database

http://string.embl.de/

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Database/URL/FTP

•DIP http://dip.doe-mbi.ucla.edu•BIND http://bind.ca •MPact/MIPS http://mips.gsf.de/services/ppi •STRING http://string.embl.de•MINT http://mint.bio.uniroma2.it/mint•IntAct http://www.ebi.ac.uk/intact•BioGRID http://www.thebiogrid.org•HPRD http://www.hprd.org•ProtCom http://www.ces.clemson.edu/compbio/ProtCom•3did, Interprets http://gatealoy.pcb.ub.es/3did/•Pibase, Modbase http://alto.compbio.ucsf.edu/pibase•CBM ftp://ftp.ncbi.nlm.nih.gov/pub/cbm•SCOPPI http://www.scoppi.org/•iPfam http://www.sanger.ac.uk/Software/Pfam/iPfam•InterDom http://interdom.lit.org.sg•DIMA http://mips.gsf.de/genre/proj/dima/index.html•Prolinks http://prolinks.doe-mbi.ucla.edu/cgibin/functionator/pronav/•Predictome http://predictome.bu.edu/

PLoS Computational Biology March 2007, Volume 3 e42

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Some comments on analysis tools: > 68 GO based analysis tools listed on the

GO Consortium website (not a comprehensive list!)

several tools combine GO, pathway and network functional analysis

many different ways of visualizing the results

expanding the species supported by analysis tools – check with tool developers

check for last updates & user support information

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Tutorial 5In this tutorial we will use several GO

modeling tools. We will use GOSlimViewer to summarize the GO function from the cassava data set. Next we will use two GO enrichment analysis tools, DAVID and AgriGO to do GO enrichment analysis of a maize data set and compare the results from the two tools.

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http://www.agbase.msstate.edu/

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