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Does my gene expression dataset contain a module network of regulatory genes? Does the network have any special features?
This recipe provides one method for creating and visualizing a module network of regulatory genes. An example use of this recipe is a case where an investigator may want to evaulate an expression dataset to find regulatory genes such as transcription factors, and then determine if they are connected in a network.
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.