Binary state model algorithm. (A) Overall methodology from gene expression to gene selection. First, an exhaustive search is used for parameter estimation of the binary state model. Then, mp, t and u parameters found are used to estimate sample and stage states in the dataset and in its permutated versions needed to estimate a stage-state profile null distribution. Gene selection is based on FDR of state-stage profiles. (B) Binary state model for samples and stages. gev stands for gene expression value. (C) Graphical example of the algorithm. Squares and rectangles represent samples and stages respectively.