Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.

TitleDiscovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.
Publication TypeJournal Article
Year of Publication2012
AuthorsGarcía-Alonso, L, Alonso, R, Vidal, E, Amadoz, A, De Maria, A, Minguez, P, Medina, I, Dopazo, J
JournalNucleic Acids Res
Date Published2012 Nov 01
KeywordsBipolar Disorder; Fanconi Anemia; Gene Regulatory Networks; Genes, Neoplasm; Genome-Wide Association Study; Genomics; Humans; Protein Interaction Mapping

Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at based on HTML5 technologies is also provided to run the algorithm and represent the network.

Alternate JournalNucleic Acids Res
PubMed ID22844098
PubMed Central IDPMC3488210