Pathway and Network Analysis Service

Cancer Stem Cell program

Veronique Voisin

veronique.voisin@gmail.com

• located at TMDT 8th floor on Tuesday

Introduction about the service:

• The Pathway and Network Analysis Service is freely available to all Cancer Stem Cell program members. High-throughput genomic experiments (e.g. gene expression, protein expression, molecular interactions, large-scale genetic screens and other omics data) lead to the identification of large gene lists. The interpretation of results and the formulation of consistent biological hypotheses from these gene lists are challenging. Computational approaches can aid interpretation by relating the gene lists to knowledge about the biological system. To help researchers interpret their results, we are developing a new consulting and analysis service for pathway and network analysis. Analysis will be conducted in close collaboration with researchers on each project (Cancer Stem Cell research program) to ensure correct input data and effective interpretation of results.

Information about Pathway and Network Analysis

• Suggested readings:
  • GSEA
    • Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50.

      http://www.ncbi.nlm.nih.gov/pubmed/16199517

  • Enrichment Map:
    • Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. Merico D, Isserlin R, Stueker O, Emili A, Bader GD. PLoS One. 2010 Nov 15;5(11):e13984.

      http://www.ncbi.nlm.nih.gov/pubmed/21085593

• What you can expect:

How to use the service

Who can use the service

• You can use the service if you are a member of Cancer Stem Cell program (http://www.cancerstemcells.ca). (Note:ask Melissa if I can use this URL). If you have large gene lists coming from large-scale 'omics' (e.g. genomics) projects that are ready to be analyzed (see section Data input requirement below), you can book an appointment with us for an initial meeting.

How to book an appointment

1. Look at the calendar below to see my available times the day you want to meet (30 min to 1 h meeting). Be aware that I'm available for meetings only on Tuesdays!

2. Send me an e-mail at veronique.voisin@gmail.com to indicate when you want to meet and the purpose of the meeting.

3. I will send you an e-mail back to confirm the appointment.
4. If we meet for the first time, I encourage you to send me a paper that best describe your work prior to our meeting.

5. You must cancel a meeting 24 hours in advance. Send an e-mail at veronique.voisin@gmail.com to cancel an appointment.

Data input requirement

• Your data should have been statistically analyzed:
  • The data should have been normalized
  • Some control quality plots should have been done:
    • Box-plot of intesity (before and after normalization)
    • Principal Component Analysis (PCA)
    • Hierarchical clustering of samples
  • An appropriate statistical test testing your hypothesis (your biolgical question) should have been performed
    • for example : moderated ttest, paired t-test, ANOVA,...
• During the first initial meeting, we are going to discuss :
  • the biological question(s) you want to answer
  • the experimental design
  • the platform you use to generate your data (e.g Affymetrix or Illumina, the chip model,...)
  • the quality controls and the input data format
• Files you need to give in order for us to do the analysis
  • a ranked file (.RNK)
    • A ranked file has only 2 columns:
      • the first column corresponds to gene EntrezIDs
      • the second column contains the statistic values corresponding for each gene:
        • the statistics values are the one that enables you to tell if a gene is significantly differentially expressed or not, it could be for example the t values if you applied a t test).
        • the table is ordered by the absolute value of the second column (decreasing order).
      • the columns have no header (no title).
      • example of a ranked file:

        • 545428	96.8182
          13433	-85.3271
          108911	66.5269
          114863	59.0384

  • an expression matrix file (.txt)

Service SOP

Standard input requirements

Calendar

How to explore an interactive Enrichment Map on your computer

Download the sofware you need (see below for download and tutorial information)

1. Cytoscape
2. Enrichment Map plugin
3. WordCLoud plugin

Explore the Enrichment map using the .cys file that we give you

• Download the .cys file
  • Put the .cys file in the directory of your choice
  • In Cytoscape, go to Open, File and browse the directories to locate your file and click Open.
• Explore the map
  • The “Parameters” tab in the “Results Panel” on the right side of the window contains a legend mapping the colours to the phenotypes and displaying the parameters used to create the map (cut-off values and data files).
  • The “Network” tab in the “Control Panel” on the left lists all available networks in the current session and at the bottom has a overview of the current network which allows to easily navigate in a network even at higher zoom levels by dragging the blue rectangle (the current view) over the network.
  • Clicking on a node (the circle that represents a gene set) will open the “EM Geneset Expression Viewer” tab in the “Data Panel” showing a heatmap of the expression values of all genes in the selected gene set.
  • Clicking on an edge (the line between two nodes) will open the “EM Overlap Expression Viewer” tab in the “Data Panel” showing a heatmap of the expression values of all genes both gene sets that are connected by this edge have in common.
  • If several nodes and edges are selected (e.g. by dragging a selection box around the desired gene sets) the “EM Geneset Expression Viewer” will show the union of all genes in the selected gene sets and the “EM Overlap Expression Viewer” will show only those genes that all selected gene sets have in common.
  • The “Geneset Summary” tab in the “Results Panel” on the right contains information about which nodes and edges are selected.

Tips

• Click on “View / Show Graphics Details” to see the map details even on low zoom-levels

Online tutorials

All the software used are freely available (open-source) and easy to install on your computer.

Gene-Set Enrichment Analysis (GSEA)

• http://www.broadinstitute.org/gsea/index.jsp :

  • Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes). We use GSEA at the first analysis step. As we will perform this analysis for you, you don't need to download GSEA.

Cytoscape

• http://www.cytoscape.org/:

  • Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data

    Download Cytoscape 2.8.0 from http://www.cytoscape.org/download.html (need to enter, name, institution, e-mail address but no account necessary) Cytoscape tutorial: http://cytoscape.wodaklab.org/wiki/Presentations/Basic

EnrichmentMap

• http://baderlab.org/EnrichmentMap

  • Enrichment Map is a visualization method for gene set enrichment results which helps quickly find general functional themes in genomics data. Enrichment Map works as a plug-in for Cytoscape. To install it, download the zipped file, move it to the Cytoscape plugin directory and unzip it.

WordCloud

• http://baderlab.org/WordCloud

  • WordCloud is a Cytsocape plugin that generates a word tag cloud from a user-defined node selection, summarizing an attribute of choice. It notably eases the interpretation of the Enrichment Map. Download the WordCloud plugin and put the file in the Cytoscape plugin directory, unzip it and put the WordCloud.jar file in the plugin directory.

GeneMANIA

• http://genemania.org

  • GeneMANIA is a free public resource that offers a simple, intuitive web interface that shows the relationships between genes in a list and analyzes and extends the list to include other related genes. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function. You also can use GeneMANIA as a Cytoscape plugin. You can find the GeneMANIA tutorial at: http://genemania.org/pages/help.jsf

List of projects

• This section summarizes the current projects, and the analysis status for each project is very regularly updated. You can see progress in the analysis of your project and see the different priorities assigned to each project.

? Link to results and reports ?