Extended Data Fig. 4: Validation of the Single-omic and Multi-omic and Parsimonious Models on TCGA. | Nature Cancer

Extended Data Fig. 4: Validation of the Single-omic and Multi-omic and Parsimonious Models on TCGA.

From: The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients

Extended Data Fig. 4

Validation of RNA gene signatures for disease survival: (a) 39 gene signature of poor survival (HR = 2.17, [1.28-3.66], logrank p = 0.0031) (b) 40 gene signature of improved survival (HR=0.74 [0.49-1.12], logrank p = 0.15) (c) Parsimonious model of clinical, DNA (CNV, INDEL, SNV), RNA gene expression and computational pathology in the original cohort used to select optimal 202 analytes (peak) for validation in TCGA. Multi-omic model performance across feature reduction steps by restricting the maximum selectable features during model training. Left y axis - Accuracy and PPV score: multi-omic model performance across feature reduction steps by restricting the maximum selectable features during model training. X axis – number of maximum features at each reduction step. Right y axis - Analyte Percent (%) Contribution: each analyte’s aggregated absolute feature weight contribution at each feature reduction step.

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