Hi,
Given a protein-protein-interaction graph (e.g., from the string data base) and an outcome of a differential expression analysis (i.e., for each gene we have its log fold-change and the associated p-value between the treatment and control), is there a graph-based algorithm that can find subgraph parts enriched with genes which log fold-change p-value is below a given cutoff?
1 answer
Given a list of differentially expressed genes, 'keypathwayminer' in cytoscape can extract the highly connected sub-network from PPI. I had used their older version and found it helpful.
Check here for app: http://apps.cytoscape.org/apps/keypathwayminer
Their recent paper: http://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-014-0099-x
To further group the sub-network, you can try 'clusterviz' app in cytoscape to get network clusters.
An application paper that uses both keypathwayminer and clusterviz: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112193
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