Dissecting systems-wide data using mixture models: application to identify affected cellular processes

摘要

BackgroundFunctional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many conditions, the proportion of differentially expressed genes is considerable, making the selection criteria a balance between the inclusion of false positives and the exclusion of false negatives.