Correlation networks identified that intersect epigenetic pathways/signaling pathways with patient specific DE genes.

<p>Connections were calculated for gene-gene pairs emanating from epigenetic pathways or genes in the Notch, SHH, or WNT pathways and genes that were Differentially Expressed in each patient.</p

Gene Networks created by Pairs with high PCC (greater than 0.7) and high hypergeometric p-value yield less experimentally verified interactions.

<p>The number of connections identified was calculated for gene pairs with high PCC and high hypergeometric p-values. These connections were then compared to those identified in the literature. Note that few connections were found to be experimentally validated.</p

Correlation networks created by using the top gene pairs for each patient.

<p>The number of connections we identified were compared to those previously described in the literature (red). Yellow indicates connections, which were identified in protein-protein interaction databases.</p

Pipeline for identifying patient-specific gene association in GBM.

<p>Our first step in our pipeline is to identify Differentially Expressed (DE) genes that are represented in 3 out of 4 algorithms. Next, we filter this DE gene list for those genes that overlapped with DE genes in the TCGA GBM Database. We then calculate the Correlation Coefficient and a hypergeometric p-value for every gene pair. Finally, by selecting the gene pairs with the highest correlation values we create a patient specific gene correlation network, which can be experimentally verified. As a starting point for our experiments, we can use the sub-networks in which, already verified connections exist in the literature.</p