Exploring combinations of dimensionality reduction, transfer learning, and regularization methods for predicting binary phenotypes with transcriptomic data

This repository contains supplementary materials for the research paper "Exploring combinations of dimensionality reduction, transfer learning, and regularization methods for predicting binary phenotypes with transcriptomic data." The materials are organized into two distinct folders: - supplementary_code: source code to reproduce the analysis AE network training AVAE network training phenotype data collection predictive modelling pipeline - supplementary_data: networks and datasets used in this study trained AE network trained AVAE network trained c-ICA network 30 transcriptomic datasets with all representations and phenotypes dataset predictive performances and signficance robustness analysi