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The top-ranked genes in the differential network were predictive of the targeted therapeutic response and prognosis of glioma patients.

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posted on 2019-11-04, 18:24 authored by Jiajun Zhang, Wenbo Zhu, Qianliang Wang, Jiayu Gu, L. Frank Huang, Xiaoqiang Sun

(A-B) The areas under the ROC curves (AUCs) were computed for both the training datasets (A) and the test datasets (B) of glioma patients. (C) Differential expression profiles of the seven identified genes in the normal and tumor tissues of glioma patients. The p-values were assessed using the one-tailed Wilcoxon rank sum test. (D) The seven identified genes were associated with the survival probability of glioma patients (N = 610). A log rank test was used to assess the significance between two curves, with a p-value less than 0.0001. (E) Statistical significance of the association of the five top-ranked genes identified by the DryNetMC with prognosis of glioma patients, in comparison with a conventional differential expression analysis method, DEseq2. Wald test p-value was used to assess the prognostic significance of each gene in the table.