PathMED: an R toolkit for single-sample molecular scoring and machine learning with omics data
The benefit of integrating a novel gene set dissection step into the analysis pipeline to resolve disease heterogeneity at the pathway level is demonstrated and the generalisability of machine learning models trained on transcriptomic scores in predicting clinical outcomes when deploying on proteomic scores is shown.