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Fig. 1 | BMC Bioinformatics

Fig. 1

From: Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

Fig. 1

Analysis results for workflows splitting multiple TCGA cohorts into TP53-mutant and non-mutant patients: a Overall survival is significantly different between TP53-mutant (red curve) and non-mutant patients (black curve) with a more favorable for non-mutant patients (gain in median survival: 2066 days, p <  0.0001, n = 9444). b The distribution of the mutations types in lung adenocarcinoma is strongly shifted towards an increase of G > T transversions in TP53 mutant compared to non-mutant patients (p = 0.0006, n = 584). c Genomic stability is quantified in terms of the overall size of somatic copy number alterations (sCNA) compared between tumor and normal. sCNA are considered as genomic amplifications above a level of 3 and as genomic deletions below a level of 1 for the signal ratio between tumor and paired normal sample. The difference between TP53 mutant and non-mutant patients is highly significant in glioblastoma multiforme (p = 0.0132, n = 379)

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