Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets
Ellrott et al. provide a means to assign patient samples from clinical trials and other cancer genome studies to published TCGA molecular subtypes. Applying machine learning to data from five different molecular platforms for 8,791 TCGA tumor samples, they contribute a public resource of 737 top classifier models, which can form the foundation for clinical assay development.