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Fig. 3 | BMC Systems Biology

Fig. 3

From: Integrative modeling of multi-omics data to identify cancer drivers and infer patient-specific gene activity

Fig. 3

FLM gene activity scores improve prediction of BYL719 drug sensitivity compared to using expression, mutation and copy number data separately. a Boxplot for PIK3CA FLM scores vs. BYL719 (PIK3CA inhibitor) sensitivity. BYL719 sensitive group has higher activity scores compared to the resistant group (t-test p <10−4). Even within the PIK3CA missense mutants (colored in red), we see that FLM GoF scores are higher in sensitive compared to resistant group (t-test p <0.0008). b Using PIK3CA FLM GoF scores to predict sensitivity, the AUC significantly improved compared to expression, mutation and copy number data separately, p<0.05. We denote by * the significance level of 0.05. c Heatmap showing the FLM activity scores for PIK3CA, PTEN and the individual data types. All values are scaled between [–1, 1]. Note that our algorithm correctly labeled PIK3CA as a GoF gene, and PTEN as a LoF gene, consistent with their classification in the literature. The color bar on top indicates the sensitivity groups for the samples (green = sensitive, black = resistant). The combined predictor of PIK3CA GoF scores and PTEN LoF scores significantly improves performance compared to combinations of individual data types, p<0.009

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