A false discovery rate approach to separate the score distributions of induced and non-induced genes

The distribution of scores for differential gene expression observed in microarray experiments give rise to the assumption that the underlying score distributions of induced and non-induced genes share wide overlapping regions. Our aim is to reconstruct this mixture not only for extremal score regions but over the whole range of scores. We propose and evaluate a method based on the theory of False Discovery Rates