Determination of the differentially expressed genes in microarray experiments using local FDR

Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile. Results: Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is availa...

• Type: Journal
• Year: 2004
• Where: BMCBI
• Authors: Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, Stéphane Robin
• Keywords: BMCBI 2004, Expressed Genes, False Positive, Local Fdr