… Multiple Comparisons and Multiple Tests Using SAS, Second Edition, written by Peter Westfall,
Randall Tobias, and Russell Wolfinger, solves both problems for you by providing cutting-…

The determination of a list of differentially expressed genes is a basic objective in many cDNA
microarray experiments. We present a statistical approach that allows direct control over …

Here we present a statistically rigorous approach to quantifying microarray expression data
that allows the relative effects of multiple classes of treatment to be compared and …

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data.
The value and familiarity of the R 2 statistic in the linear univariate model naturally creates …

Microarray-based expression profiling experiments typically use either a one-color or a two-color
design to measure mRNA abundance. The validity of each approach has been amply …

Geminiviruses are small DNA viruses that use plant replication machinery to amplify their
genomes. Microarray analysis of the Arabidopsis (Arabidopsis thaliana) transcriptome in …

This article provides a unified discussion of a useful collection of heterogeneous covariance
structures for repeated-measures data. The collection includes heterogeneous versions of …

Background Gene expression profiling is being widely applied in cancer research to identify
biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for …

The rat has been used extensively as a model for evaluating chemical toxicities and for
understanding drug mechanisms. However, its transcriptome across multiple organs, or …

Background Reproducibility is a fundamental requirement in scientific experiments. Some
recent publications have claimed that microarrays are unreliable because lists of differentially …