Figure 1

Methodology for application of EPSA. A. For each perturbation in the training compendium, replicate log₂ expression of treated vs. untreated cells were analyzed. B. For each perturbation, Significance Analysis of Microarrays (SAM) [4] software was applied to identify genes with significantly altered expression. Median values among the replicates of log₂(treated/untreated) were used to represent genes in a signature. C. These values were correlated with test profiles. A false discovery rate was calculated for each perturbation, for the average level of correlation with disease profiles. D. For those signatures with a statistically significant level of correlation, survival analysis was performed using the EPSA score, or the degree of signature correlation, as a factor influencing survival. Survival analysis was carried out using the survival package in R.