Overview of classifier generation, testing and downstream analysis.

<p>Colored boxes (gray/green) depict different training data sets. Step 1- assessment of individual machine-learning tools vs LPS; Step 2– assessment of machine-learning tool combinations; Step 3–assessment of classifier gene sets, training on GSE10846_R-CHOP, and testing on previously seen and unseen data sets: Step 4- further assessment on unseen data sets; Step 5– classification of additional data sets, evaluation of differential gene expression in all-by-all comparison, downstream analysis with meta-profiles and enrichment of molecular signatures.