Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)
Description
The Power Law Global Error Model (PLGEM) has been shown to faithfully model
the variance-versus-mean dependence that exists in a variety of genome-wide
datasets, including microarray and proteomics data. The use of PLGEM has been
shown to improve the detection of differentially expressed genes or proteins in
these datasets.