Tutorial_Part3_final - Bioinfo-casl
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Transcript Tutorial_Part3_final - Bioinfo-casl
Tutorial session 3
Network analysis
Exploring PPI networks using Cytoscape
EMBO Practical Course Session 8
Nadezhda Doncheva and Piet Molenaar
Overview
Focus: Network analysis
Identify active subnetworks
Analyze Gene Ontology enrichment
Perform topological analysis
Find network clusters
Find network motifs
Concepts
Enrichment
Clustering
Guild by association
Data
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Stored sessions; Drosophila and Neuroblastoma
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Identify active subnetworks
jActiveModules plugin
Active modules are sub-networks that show differential
expression over user-specified conditions or time-points
Microarray gene-expression attributes
Mass-spectrometry protein abundance
Input: interaction network and p-values for gene
expression values over several conditions
Output: significant sub-networks that show differential
expression over one or several conditions
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jActiveModules (Demo)
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Use case; Assignment 3.1
Using neuroblastoma cell lines inhibitors to elucidate
important pathways
2 neuroblastoma cell lines: SHEP21, SY5Y
7 inhibitors
Profiled on Affymetrix array
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http://r2.amc.nl
Other resource e.g. GEO
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Use case; Assignment 3.1
Systematic perturbations
Different cell-lines
Including controls: DMSO
97 arrays: data collected from R2: hugo-once etc
PI3K-dependent
Cell lines
-SY5Y
-D425
PIK90
RAS/ERK-dependent
Cell lines
-SHEP2
-RD
Harvest: RNA Affy (97samples)
protein WB
PI3K signature
RAS/ERK signature
RAS
RAF
U0126
PI3K
PI103
AKTi 1/2
MK2206
AKT
MEK
mTORC1
mTORC2
ERK
Rapamycin
PP242
Use case; Assignment 3.1
1.
Open the Neuroblastoma session and load the pvalues
from this experiment
2.
Run jActiveModules on the annotated network
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1.
What regions are important?
2.
Can you imagine any caveats for this method?
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Gene Ontology
Provides three structured
controlled vocabularies
(ontologies) of defined
terms representing gene
product properties:
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Biological Process (23074
terms): biological goal or
objective
Molecular Function (9392
terms): elemental
activity/task
Cellular Component (2994
terms): location or complex
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Analyze Gene Ontology enrichment
BiNGO plugin:
http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html
Calculates over-representation of a subset of genes with
respect to a background set in a specific GO category
Input: subnetwork or list, background set by user
Output: tree with nodes color reflecting
overrepresentation; also as lists
Caveats: Gene identifiers must match; low GO term
coverage, background determining
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BiNGO (Demo)
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Use case; Assignment 3.2
Open the Neuroblastoma session and run BiNGO on
the filtered network.
1.
1.
What categories are enriched?
2.
Can you find these back in the article?
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Compute topological parameters
NetworkAnalyzer plugin: http://med.bioinf.mpiinf.mpg.de/netanalyzer/
Computes a comprehensive set of simple and complex
topological parameters
Displays the results in charts, which can be saved as
images or text files
Can be combined with the ShortestPath plugin
http://www.cgl.ucsf.edu/Research/cytoscape/shortestPath/i
ndex.html
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NetworkAnalyzer (Demo)
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Identify hubs
CytoHubba plugin:
http://hub.iis.sinica.edu.tw/cytoHubba/
Computes several topological node parameters
Identifies essential nodes based on their score and
displays them in a ranked list
Generates a subnetwork composed of the best-scored
nodes
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CytoHubba (Demo)
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Use case; Assignment 3.3
Open the Drosophila network session
Check the network parameters
1.
1.
Is it scale free?
2.
Can you find important players?
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Find network clusters
Network clusters are highly interconnected sub-networks
that may be also partly overlapping
Clusters in a protein-protein interaction network have
been shown to represent protein complexes and parts of
biological pathways
Clusters in a protein similarity network represent protein
families
Network clustering is available through the MCODE
Cytoscape plugin: http://baderlab.org/Software/MCODE
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MCODE & ClusterMaker (Demo)
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Use case; Assignment 3.4
Open the Drosophila session
1.
Run the MCODE algorithm
2.
Run the MCL clustering algorithm
1.
Compare the results
2.
Can you corroborate some of the clusters found in the
article?
3.
Are there additional filtering options?
4.
Play with the settings and observe their influence
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Find network motifs
NetMatch plugin:
http://alpha.dmi.unict.it/~ctnyu/netmatch.html
Network motif is a sub-network that occurs significantly
more often than by chance alone
Input: query and target networks, optional node/edge
labels
Output: topological query matches as subgraphs of target
network
Supports: subgraph matching, node/edge labels, label
wildcards, approximate paths
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NetMatch (Demo)
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Use case; Assignment 3.5
1.
In the Drosophila session try to find a feedforward
motif
2.
Finally toy around with the settings of the Vizmapper to
produce a nice paper-ready figure!
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Other Useful Plugins
PSICQUICUniversalClient
AgilentLiteratureSearch
GeneMANIA
CyThesaurus
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structureViz
ClusterMaker
EnrichmentMap
PiNGO
ClueGO
RandomNetworks
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Wrapping up…
Biological questions
I have a protein
I have a list of proteins
Function, characteristics from
known interactions
Shared features, connections
I have data
Derive causal networks
Network
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Topology
Hubs
Clusters
New hypotheses
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End!
And a final note…..
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Announcing Cytoscape 3.0 Beta
Easier data import
Improved user experience
Graphical annotations
One-click install from AppStore
Improved API for app developers
http://cytoscape.org