Skip to main content
Fig. 15 | BMC Bioinformatics

Fig. 15

From: Prioritization of cancer driver gene with prize-collecting steiner tree by introducing an edge weighted strategy in the personalized gene interaction network

Fig. 15

Overview of paired-SSN for constructing personalized weight gene interaction networks for a given cancer patient, TCGA-BH-A0B5 in BRCA cancer data. For a given cancer patient, we firstly chose the expression data of all normal samples in BRCA as the reference data and constructed the co-expression network of tumor sample (white color) and normal sample (green color) respectively with the reference data by using SSN method. Then the personalized weighted gene interaction network was constructed by using significant interactions where the co-expression P-value of of tumor sample is less than (or greater than) 0.05, and that greater than (or less than) 0.05 of normal sample. Furthermore, we extracted the edge weights of significant interactions by doing the log2 operation on the ratio of the two weights. The edge weights indicate transition degree value of significant personalized gene interactions between the normal state and tumor state of an individual patient. Here we showed the individual specific sub-networks related with driver gene ITGA5 which contain its first-order neighboring genes as an example

Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us