Analysis of oligonucleotide array experiments with repeated measures using mixed models

Background: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. Results: In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH...

• Type: Journal
• Year: 2004
• Where: BMCBI
• Authors: Hao Li, Constance L. Wood, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg
• Keywords: BMCBI 2004, Expressed Genes, Linear Mixed Model, Microarray Data Analysis