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

@article{citeulike:2390667, abstract = {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 available at http://www.inapg.fr/ens\_rech/mathinfo/recherche/mathematique/outil.html. Conclusions The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene) or genes pertaining to the same regulation network or the same chromosomic region.}, author = {Aubert, J. and Bar-Hen, A. and Daudin, J. J. and Robin, S. }, citeulike-article-id = {2390667}, journal = {BMC Bioinformatics}, keywords = {fdr, microarray}, pages = {125+}, posted-at = {2008-02-17 13:53:20}, priority = {0}, title = {Determination of the differentially expressed genes in microarray experiments using local FDR}, url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=520755}, volume = {5}, year = {2004} }

TY - JOUR ID - citeulike:2390667 L3 - citeulike-article-id:2390667 TI - Determination of the differentially expressed genes in microarray experiments using local FDR JF - BMC Bioinformatics VL - 5 SP - 125 N2 - 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 available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. Conclusions The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene) or genes pertaining to the same regulation network or the same chromosomic region. KW - fdr KW - microarray AU - Aubert, J AU - Bar-Hen, A AU - Daudin, JJ AU - Robin, S PY - 2004/// UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=520755 ER -