Within-group variability, i.e., the variability between replicates, is modeled by the dispersion parameter αi, which describes the variance of counts via \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $\operatorname {Var} K_{\textit {ij}} = \mu _{\textit {ij}} + \alpha _{i} \mu _{\textit {ij}}^{2}$ \end{document}VarKij=μij+αiμij2. Accurate estimation of the dispersion parameter αi is critical for the statistical inference of differential expression. For studies with large sample sizes this is usually not a problem. For controlled experiments, however, sample sizes tend to be smaller (experimental designs with as little as two or three replicates are common and reasonable), resulting in highly variable dispersion estimates for each gene. If used directly, these noisy estimates would compromise the accuracy of differential expression testing.
