Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Background: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are o...