Download COST Functional Modeling Workshop

Pathways & Networks
analysis
COST Functional Modeling Workshop
22-24 April, Helsinki
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
Pathways & Networks
• A network is a collection of interactions
• Pathways are a subset of networks
(Pathways are a 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
1. Pathways analysis enables:
• Analysis of data in the context of molecular
mechanisms to move beyond statistical analysis of
expression to novel biological insights
• Applying biological filters to focus in on the changes
most relevant to experimental model
• Comparison of affected pathways and phenotypes
across platform, time, dose etc
(www.ingenuity.com)
What regulatory relationships
exist between the genes,
proteins in my dataset?
Networks
Which biological and disease
processes are most relevant to
my genes of interest?
Functional
analysis
Which well-characterized cell
signaling and metabolic
pathways are most relevant to
my experimental data?
Metabolic
and
Signaling
pathways
http://www.ingenuity.com
Pathways Resources
Pathguide – the pathway resource list
http://www.pathguide.org
KEGG
Reactome
BioCyc
BioCarta
GenMAPP
http://www.genome.jp/kegg/pathway.html
http://www.reactome.org
http://www.biocyc.org
http://www.biocarta.com
http://www.genmapp.org
Pathways Analysis Guide
• Is there commercial pathways analysis
software available at your institute?
• For commercial/Free pathways packages:
what species do they support
• your species or finding orthologs for a
supported species
• What accession type do you need to use?
• How complete is your analysis likely to be
(are both signaling & metabolic pathways
represented, how many pathways, how
many of your gene products can be
analyzed?).
2. Biological Networks
• Networks often represented as graphs
• Nodes represent proteins or genes that code for
proteins
• Edges represent the functional links between
nodes (e.g. regulation or binding)
• Small changes in graph’s topology/architecture
can result in the emergence of novel properties.
Types of interactions
• protein (enzyme) – metabolite (ligand)
• metabolic pathways
• protein – protein
• cell signaling pathways, protein complexes
• protein – gene
• genetic networks
Network example: STRING Database
http://string.embl.de/
Sod1
Mus musculus
Database/URL/FTP
PLoS Computational Biology March 2007, Volume 3 e42
•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/
Cytoscape
Cytoscape is a freely-available (open-source,
java-based) bioinformatics software platform for
• visualizing biological networks (e.g. molecular
interaction networks) and
• analyzing networks with gene expression
profiles and other data
http://www.cytoscape.org/
Cytoscape Core Features
• Customize network data display using
visual styles
• Powerful graph layout tools
• Easily organize multiple networks
• Easily navigate large networks
• Filter the network
• Plugin API (“apps”)
Cytoscape includes a flexible plugin architecture
that enables developers to add extra
functionality beyond that provided in the core:
Some Cytoscape Plugins
• jActiveModules: identify significant “active” subnetworks
• Expression Correlation Network: cluster expression data
• Agilent Literature Search: build networks by extracting
interactions from scientific literature.
• MCODE: finds clusters of highly interconnected regions in
networks
• cPath: query, retrieve and visualize interactions from the
MSKCC Cancer Pathway database
• BiNGO: determine which Gene Ontology (GO) categories are
statistically over-represented in a set of genes
• Motif Finder: runs a Gibbs sampling motif detector on
sequences for nodes in a Cytoscape network.
• Exhaustive list at:
• http://chianti.ucsd.edu/cyto_web/plugins/index.php
Gene Ontology enrichment analysis
BiNGO plugin
Bingo Plugin – uses GO structure to
visualize results.
http://www.agbase.msstate.edu/hpi/main.html
Networks Analysis Guide
• Is there commercial networks analysis software
available at your institute?
• Can it be combined with pathways analysis?
• For commercial/free software: what species do
they support
• your species or finding orthologs for a supported
species
• What accession type do you need to use?
• How complete is your analysis likely to be (how much
interaction data exists for your species, how many of
your gene products can be analyzed?).
• Host-Pathogen Interactions – as a special cases of
interaction data.
Pathways and Networks – what next?
Exercises or working on your own data sets:
• Working on your own data set
• continue with enrichment analysis, etc
• Can you find tools that do enrichment analysis and
pathways/network analysis?
• Tutorial 5: Pathways & network analysis
• Use tutorial to try different tools – compare,
determine which will work for you data set.