Pallocca, Matteo Angeli, Davide Palombo, Fabio Sperati, Francesca Milella, Michele Goeman, Frauke Nicola, Francesca Fanciulli, Maurizio Nisticò, Paola Quintarelli, Concetta Ciliberto, Gennaro MOESM5 of Combinations of immuno-checkpoint inhibitors predictive biomarkers only marginally improve their individual accuracy Additional file 5: Figure S1. High level workflow for ICI biomarker validation and combination. The N biomarkers were individually tested for each dataset, this test serving as a primary validation of the proposed performance. Mean accuracy was computed for each classifier in all available datasets. Combinatorial analysis was carried out with majority voting and Generalized Linear Models. The E[X] formula stands as an example of the model to create when estimating the a0…aN linear factors. Immuno-checkpoint inhibitors biomarkers;Genomics;Immunotherapy;ImmunoPhenoScore;TIDE;RNA-seq;Exome sequencing;Majority voting;Generalized linear models 2019-04-23
    https://springernature.figshare.com/articles/presentation/MOESM5_of_Combinations_of_immuno-checkpoint_inhibitors_predictive_biomarkers_only_marginally_improve_their_individual_accuracy/8032733
10.6084/m9.figshare.8032733.v1