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Tutorial session 2
Network annotation
Exploring PPI networks using Cytoscape
EMBO Practical Course Session 8
Nadezhda Doncheva and Piet Molenaar
Overview
Focus: Network annotation and visualization
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Loading and manipulating attributes
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Identifier mapping
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Mapping data onto the network
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Use visuals to convey data
Concepts
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Vizmapper
Data
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Human Neuroblastoma mutated genes list
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Attributes
Nodes and edges can have
attributes associated with
them
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Gene expression data
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Mass spectrometry data
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Protein structure information
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Gene Ontology terms, etc.
Cytoscape supports multiple
data types: Numbers, Text,
Logical, Lists...
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Loading attributes
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Use pre-formatted attribute files
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Import attribute from table
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Excel file
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Comma or tab delimited text
Import attribute from web services
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NCBI Entrez Gene
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Ensembl Biomart
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Use ‘import attribute or expression matrix’
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Create attributes manually in the attribute browser
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Loading attributes from table (Demo)
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Use Case 2.1: Neuroblastoma
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Childhood neuro endocrine tumor
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Young children
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Variable clinical outcome
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Low stages
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Good prognosis
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Numeric changes of chromosomal copy numbers
High stages
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Poor prognosis
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Structural chromosomal defects (LOH1p / 11q etc)
Few gene defects identified
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MYCN amplification (20%)
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ALK activation (7%)
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CCND1 / PHOX2B / NF1
Use Case 2.1: Neuroblastoma
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Poor prognosis
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Subgroup (~1/3) characterized by MYCN amplification
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Rest unknown
Use case: Assignment 2.1
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Whole genome sequence of 86 tumor vs blood
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1043 genes with mutations
1.
Load the list of genes
(neuroblastoma_mutated_symbols.txt) as a network
2.
Use the tab separated dataset
(neuroblastoma_mutated_annotations.txt) to map
additional information
1.
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Make sure the attributes have informative names
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Assignment 2.1 results
Load the list; use the
same importer
1.
1.
Load the annotations
2.
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No interactions yet
1.
Check text import
settings
2.
Check mapping settings
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Attribute management
Different type of attributes: Strings, Numbers, …
Select attributes for display
Node or Edge ID
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Specific Attribute Tabs: for Nodes, Edges, and Network
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Tips & Tricks: Root Graph and sessions
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”There is one graph to rule them all...”
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The networks in Cytoscape are all ”views” on a single
graph.
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Changing the attribute for a node in one network will
also change that attribute for a node with the same ID in
all other loaded networks
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There is no way to ”copy” a node and keep the same ID
 Make a copy of the session
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Identifier mapping
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Identifiers (IDs) are ideally unique, stable name or numbers
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But: too many IDs and different database records for Gene, DNA,
RNA, Protein
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The ID Mapping challenge:
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Avoid errors by mapping IDs correctly
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Gene names are ambiguous
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Excel introduces errors
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Problems reaching 100 % coverage
Recommendations (for proteins and genes):
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Map everything to Entrez Gene IDs using a spreadsheet
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Manually curate missing mappings to achieve 100 % coverage
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Be careful of Excel auto conversions
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Identifier mapping (Demo)
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Use case: Assignment 2.2
1.
Use the Biomart plugin to map UniProt identifiers on
the genes
http://cytoscape.org/manual/Cytoscape2_8Manual.html#Node Name Mapping
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Assignment 2.2 results
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Use the Ensemble 68 set
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Input data type is HGNC
symbols
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Import more than just the
UniProt IDs
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Data mapping
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Mapping of data values associated with graph elements
onto graph visuals
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Data mapping
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Visual attributes
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Node fill color, border color, border width, size, shape, opacity,
label
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Edge type, color, width, ending type, ending size, ending color
Mapping types
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Passthrough (labels)
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Continuous (numeric values)
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Discrete (categories)
Visual style
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VizMapper
List of Visual Styles
Default Visual
Style editor
List of Data attributes
List of Visual attributes
Mapping definition
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Data mapping (Demo)
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Tips & Tricks: Data mapping
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Avoid cluttering your visualization with too much data
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Map the data you are specifically interested in to call out
meaningful differences
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Mapping too much data to visual attributes may just
confuse the viewer
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Create multiple networks and map different values
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Use case: Assignment 2.3
1.
Map the size of the nodes to the number of
occurrences
2.
Map color to the tumor ids
1.
Hint: use a rainbow pattern
http://cytoscape.org/manual/Cytoscape2_8Manual.html#Visual Styles
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Assignment 2.3 results
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Use gradient
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Readily shows higher
number of mutations
Use rainbow
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Similar names, similar
colors
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Assignment 2.3 results
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Exploring expression data
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VistaClara plugin
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Exploratory data analysis of multi-experiment microarray
studies
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A graphical and interactive alternative to the standard attribute
browser
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VistaClara (Demo)
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Filtering & editing data
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Use filters
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QuickFind nodes and edges
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Index the network based on a node or edge attribute
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Dynamic filtering for numerical attributes
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Build complex filters using AND, OR, NOT relations
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Define topological filters (considers properties of near-by
nodes)
Create subnetworks
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Filtering & editing data (Demo)
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Use case: Assignment 2.4
1.
What is the gene with most mutations?
2.
Filter the network for genes with more than one
mutation (why?) and save the new network.
3.
Use the Bisogenet plugin...
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...to find interactions among these
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...to find interactions among these and their first neighbours
(or explore different settings of Bisogenet according to your
taste)
4.
Store your session for later use
http://cytoscape.org/manual/Cytoscape2_8Manual.html#Finding and Filtering Nodes and Edges
http://bio.cigb.edu.cu/biso/BisoGenet_User_Manual.pdf
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Assignment 2.4 results
MYCN
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2.
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Frequently amplified; no
additional information
More likely not to be
bystander
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Assignment 2.4 results
MYCN
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Frequently amplified; no
additional information
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More likely not to be
bystander
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Bisogenet
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Between: Only large
genes
2.
Neighbours: Promising
hairball
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To be continued…
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Build, visualize and analyze your own network with
Cytoscape
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Network generation
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Network annotation and visualization
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Network analysis
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Identify active subnetworks
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Analyze Gene Ontology enrichment
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Perform topological analysis
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Find network clusters
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Find network motifs
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