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"Cross-Platform Omics Prediction Procedure: a game changer for implementing precision medicine"
presented by Professor Jean Yang, University of Sydney.
In this modern era of precision medicine, molecular signatures identified by advanced omics technologies hold great promise to better guide clinical decisions. However, current approaches are often location-specific due to the inherent differences between platforms and across multiple centres, thus limiting the transferability of molecular signatures. I will present Cross-Platform Omics Prediction (CPOP), a penalised regression model that can use omics data to predict patient outcomes in a platform-independent manner and across time and experiments. CPOP improves on the traditional prediction framework of using gene-based features by selecting ratio-based features with similar estimated effect sizes. These components gave CPOP the ability to have a stable performance across datasets of similar biology, minimising the effect of technical noise often generated by omics platforms. We also present a comprehensive evaluation to demonstrate its potential to be used as a critical part of a clinical screening framework for precision medicine.
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