Modern molecular biology data present major challenges for the statistical methods that are used to detect differential expression, such as the requirement of multiple testing procedures and increasingly, empirical Bayes or similar methods that share information across all observations to improve inference. For microarrays, the abundance of a particular transcript is measured as a fluorescence intensity, effectively a continuous response, whereas for digital gene expression (DGE) data the abundance is observed as a count. Therefore, procedures that are successful for microarray data are not directly applicable to DGE data.
