Previous Recipe Version: 3

Saved about 4 years ago on 07/19/2016 17:40:51 UTC by sgaramsz
This version's status was: Published
Genomica cytoscape

Create and visualize a module network of regulatory genes

Added by sgaramsz on 2015.05.22 Official logo
Last updated on over 3 years ago.


Summary

 

This recipe provides one method for creating and visualizing a module network of regulatory genes. In particular, the regulatory genes of interest are genes which regulate other genes associated with an embryonic stem cell (ESC) state. This 'stemness signature' is a feature common to ESCs, as well as induced pluripotent stem cells (iPSCs), and also in a compendium of human cancers, such as breast cancer. This recipe recapitulates research by Wong et al., in Cell Stem Cell (2008), "Module map of stem cell genes guides creation of epithelial cancer stem cells."

We use a gene expression dataset of primary human breast cancer tumor samples (described in Chin, K. et al, Cancer Cell, 2006), and create a module network by projecting a set of stemness regulators onto the gene expression dataset, using Genomica. A module network is a model which identifies regulatory modules from gene expression data, especially modules of co-regulated genes and their regulators. The module also identifies the conditions under which the regulation can occur.

After obtaining the module network, we visualize it using Cytoscape. Since the network is very large, we then filter it to just a subnetwork of stemness regulators and their connections, again using Cytoscape. This provides us with a visual representation of the stemness regulators as they appear projected onto a breast cancer tumor dataset.

 

Inputs

To complete this recipe, we will need a gene expression dataset and a list of genes which we believe to be important transcriptional regulators. In this example, we use a gene expression dataset of primary human breast cancer tumor samples, which is fully described in Chin, K. et al, Cancer Cell (2006). We also use a set of genes which are believed to be regulators of the embryonic stem cell state, called "stemness regulators". This gene set of stemness regulators can be obtained by following the recipe for completing Stepwise Linkage Analysis of Microarray Signatures (SLAMS). We will need the following datasets, which can be downloaded from GenomeSpace's Public folder:

 

breasttumor.preprocessed.collapsed.tab
This file contains the gene expression profile of primary human breast cancer tumor samples. The original dataset has been log-transformed, row-centered on the mean, and has had the probe IDs collapsed to HUGO Gene Symbols.
stemness_regulators.geneset.tab
This file contains a list of genes which are believed to regulate genes associated with the embryonic stem cell state.

 

Getting Data

  1. Log into GenomeSpace.
  2. Navigate to the following Public data folder: Public > RecipeData.
  3. The following files will be used for this recipe, in the following folders:
    1. breasttumor.preprocessed.collapsed.tab: ExpressionData
    2. stemness_regulators.geneset.tab: GeneSets

Outputs

A subnetwork of genes which regulate the transcription of embryonic stem cell-associated signature genes. This subnetwork shows the connections between regulators of this 'stemness signature'.

Recipe steps

  • Genomica
    1. Create a module network of co-regulated genes
  • Cytoscape
    1. Visualize the gene regulatory network
    2. Filter the network of nodes and edges to just the stemness regulators
    3. Exploring the subnetwork

  1. Launch Genomica on the normalized breast cancer gene expression dataset file (breasttumor.preprocessed.collapsed.tab).
  2. Navigate to the following menu: Algorithms > Create a Module Network…
  3. Once the tool has loaded, change the following parameters:
    1. Under Regulation, set Maximum tree depth to 5.
    2. For Candidate regulator genes, click GenomeSpace Load….
    3. Choose the stemness regulators gene set (stemness_regulators.geneset.tab), then click Select.
      NOTE: Once the list of genes is loaded, the number of candidate regulators genes will change (see image below).
  4. Click Run to create a module network.

    NOTE: It may take several minutes to learn and generate the module network.
  5. Export the resulting network to GenomeSpace using the following steps:
    1. Navigate to the following menu: GenomeSpace > Export Network to GenomeSpace…

      NOTE: A pop-up will appear indicating that you should save the file with a .ndb extension. Click OK to close the pop-up and continue with the export (see below).
    2. Choose a directory to save the file to.
    3. Give the file a name, e.g. stemness_network.ndb.
    4. Click Save As.
  6. Close Genomica and return to GenomeSpace.
  1. Launch Cytoscape from GenomeSpace.
  2. Load the stemness network into Cytoscape using the following steps:
    1. Navigate to the menu: File > Import > GenomeSpace > Load Network…
    2. Choose the stemness network file (stemness_network.ndb)
    3. Once the network is loaded, navigate to the following menu: Control Panel > Network.
    4. Right-click on the stemness_network, and choose Create View.

This will create a network of 13,341 nodes and 117,815 edges. This is an incredibly large, dense network. It is best to filter the network before attempting to visualize it using a different Cytoscape layout, such as a force-directed layout or a degree-sorted circular layout. In the next step, we will filter the network to a more manageable size.

  1. Load the list of stemness regulators into Cytoscape using the following steps:
    1. Navigate to the menu: File > Import > GenomeSpace > Load Attributes from Table…
    2. Choose the stemness regulators file (stemness_regulators.geneset.tab).
    3. Under the Advanced section, check the box next to Show Text File Import Options.
    4. Under the Attribute Names section, check the box next to Transfer first line as attribute names.
    5. Click Import to import the file.
    6. A dialog box will appear once the file has been imported. Click Close to close the dialog box.
  2. Under the Control Panel section, click the Filters tab.
  3. Under the Filter Definition section, use the drop-down menu to choose node.INGENESET as the attribute to filter on.
  4. Click Add to add the filter.
  5. Under the Advanced section, double-click on the bar next to the INGENESET attribute, and change the following parameters:
    1. Low bound: 1
    2. High bound: 1
    3. Click OK

      NOTE: This will select the stemness regulators in the existing network. They will appear highlighted in yellow if they are a stemness regulator. Make sure not to accidentally de-select the highlighted nodes by clicking in the visualization panel. If you do accidentally de-select the nodes, you can re-select them by clicking the button.
  6. In the main Cytoscape menu, click on the following menu icon:
    This is the icon indicating the tool, Create new network from selected nodes, all edges. This will create a new subnetwork with just the stemness regulators and their connections. You should obtain a network of 48 nodes and 334 edges.
  • Cytoscape provides many options for displaying a network. For example:
    • A force-directed layout finds an optimal way to display nodes and edges by simulating nodes as objects and edges as springs connecting objects together. Cytoscape provides several variations on a force-directed layout. To create a force-directed layout, try the following:
      Layout > Cytoscape Layouts > Edge Weighted Force Directed (BioLayout) > All Nodes > unweighted
    • A circular layout arranges nodes in a circle. Layouts can use information about a node, such as the node's degree, to determine the order of nodes within the circle. To create a circular layout, try the following:
      Layout > Cytoscape Layouts > Circular Layout > All Nodes
    • You can also sort a circular layout using features of the nodes, e.g. the degree or connectivity of the nodes. By creating a degree-sorted circular layout (see the results section), you can visualize all nodes and edges with minimal overlap, and can easily identify which nodes have the most or least connections.
      Layout > Cytoscape Layouts >  Degree Sorted Circle Layout
  • To control the density of the network (how far nodes are from one another), you can use the Scale function. Select Layout > Scale, then use the sliding scale bar to increase or decrease network density.
  • To change the visual style of the network, e.g., by coloring nodes or adding arrows to edges, navigate to the VizMapper™ tab in the Control Panel. You can choose preset styles using a drop-down menu. You can create your own styles by clicking on the Defaults pane, then adjusting the parameters.
    For example, to adjust edge color first choose the Edge tab in the bottom part of the pane. Then click on EDGE_COLOR, choose a new color, and click OK. Some variables take numeric inputs, such as EDGE_LINE_WIDTH.

Results Interpretation

This is an example interpretation of the results from this recipe. First, we created a module network of genes that regulate the stemness signature, by projecting it onto a breast cancer tumor gene expression dataset using Genomica. We then used Cytoscape to visualize the connections between these genes, and to filter a large network down into a subnetwork of just stemness regulators.

We can see from the resulting subnetwork (see below) that, e.g. genes such as POLR2K and MYC are stemness regulators with many connections to other stemness regulators. In contrast, genes such as SQLE or PSCA have fewer connections to other stemness regulators. We can describe POLR2K and MYC as having higher 'degree', than genes such as SQLE or PSCA. These connections in the network imply that perturbing the regulation of POLR2K or MYC would have a larger effect on the embryonic stem cell expression signature (because their multiple connections allow perturbations to propagate in the network) than perturbing other genes that have fewer connections.


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