R2 and Cytoscape: Inferring gene targets by graph based integration and analysis of molecular biological data

Piet Molenaar

Academic Medical Center, University of Amsterdam, the Netherlands

Biological Use Case: In our lab we're doing research into the molecular networks involved in childhood cancer. To this end we've profiled a large set of childhood tumors. Guided by biological questions we set out to develop a web-based array analysis platform called R2. In order to make an educated guess what genes to test that appeared of importance in this analysis we needed additional network analysis.


Cytoscape version: 2.4 - 2.6

Plugins to Load: R2Plugin, NetMatch

GUI steps:




1. Research into childhood tumors. Array data analyzed using web-based R2. Biologists use tumor series to extract relevant genes. These are manipulated in tumor cell-lines using siRna and studied in time-series

Open website: http://hgserver1.amc.nl/cgi-bin/r2/main.cgi

2. Access and datasets input still restricted; will change. For logon mail r2-support_at_amc.uva.nl

Logon with: un pw

If problem use the session file below (Piet: todo provide restricted access logon)

3. R2 portal shows; menu reflects all possibilities, lots of data (>17,000 arrays), clinical data, all types of stat analysis


4. Note based on

Click timeseries

5. Panel provides you with three choices: Explore timeseries: single gene in series; TableBuilder: Find genes in series based on tresholds; Multiplo: Limma statistics applied to replicates. Availability of other datasets under dropdown

Select TableBuilder

Keep default selection set_hg_mix, upcoming improved naming of these sets

6. Tree reflects the cell-lines

Choose cellline imr

7. Under cell-line the manipulated genes and type of manipulation; multiple selection possible

Choose Notch1

Multiple selection is tricky!

8. There are several cut-offs and tresholds to set, hugoonce, guarantees only one hugo per probeset; create networks, creates the cytoscape network

Set hugoonce, create networks, use manipulated gene to yes. Set cutoff to 100, logfold to 1

9. List of regulated genes is created. Now create a network

Click on button

If not running webstart is created

10. We selected treat gene as node so it is treated as network, Note time points layout

11. Now gather extra knowledge; protein notch3 upregulated, what influence has this on the transcription factor regulatory network, ie: what tf regulate targets downstream in time and have binding partners present; Hard for biologist typical computational task

Click Plugins->TF partner analysis->Add time causal network

If people want to: show code, note att names

12. Do some vizmapping

Create vizmapping edge color for Tf-interaction attribute; has two discrete values

Binding partners red, TF sites green

13. Do some filtering

Create greater 3 neighbours filter, select and deselect source node...

14. Open netmatch; netmatch has a graph query facility enabling you to draw a query including attribute values

Click the pencil icon in the top-bar of the netmatch panel

15. Create / load query network

Draw a network three nodes; one in the middle having two edges; Add att values by right clicking on edges: 'NCBI-TF-Interaction' any direction; 'Transcription factor binding sites' outgoing. Click on the 'pass query' button

Query network inc atts can be downloaded below

16. Now the query is performed

Set att names for nodes to id, for edges to Tf-Interaction

17. In the results panel the resulting subnetworks appear

Enable the create subnetwork box, click on one of the result networks, set vizmap to timeseries in vizmapper

18. We now have a biological relevant network of a TF having a binding partner present and regulating a target downstream

Note that additional logic can be incorporated; up/down etc

Data Files: Supplied via website R2. Sample session file: Notch3ICFiltered Netmatch query files: EdgeAtts, NodeAtts, NetmatchQuery sif file

Presentation: R2AndCytoscape_PPT

Webstart: Time permitting

Video: Time permitting

R2InferGeneTargetsRecipe (last edited 2009-02-12 01:03:01 by localhost)

Funding for Cytoscape is provided by a federal grant from the U.S. National Institute of General Medical Sciences (NIGMS) of the Na tional Institutes of Health (NIH) under award number GM070743-01. Corporate funding is provided through a contract from Unilever PLC.

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