Inference on the limiting false discovery rate and the p-value threshold parameter assuming weak dependence between gene expression levels within subject Journal Article
| Authors: | Heller, G.; Qin, J. |
| Article Title: | Inference on the limiting false discovery rate and the p-value threshold parameter assuming weak dependence between gene expression levels within subject |
| Abstract: | An objective of microarray data analysis is to identify gene expressions that are associated with a disease related outcome. For each gene, a test statistic is computed to determine if an association exists, and this statistic generates a marginal p-value. In an effort to pool this information across genes, a p-value density function is derived. The p-value density is modeled as a mixture of a uniform (0,1) density and a scaled ratio of normal densities derived from the asymptotic normality of the test statistic. The p-values are assumed to be weakly dependent and a quasi-likelihood is used to estimate the parameters in the mixture density. The quasi-likelihood and the weak dependence assumption enables estimation and asymptotic inference on the false discovery rate for a given rejection region, and its inverse, the p-value threshold parameter for a fixed false discovery rate. A false discovery rate analysis on a localized prostate cancer data set is used to illustrate the methodology. Simulations are performed to assess the performance of this methodology. Copyright ©2007 The Berkeley Electronic Press. All rights reserved. |
| Keywords: | controlled study; genetics; methodology; prostate specific antigen; gene expression; prostate cancer; confidence interval; simulation; prostate-specific antigen; prostatic neoplasms; statistical analysis; statistical significance; microarray analysis; oligonucleotide array sequence analysis; models, statistical; prostate tumor; prediction and forecasting; predictive value of tests; dna microarray; microarray; statistical model; density functional theory; genetic algorithm; likelihood functions; quasi experimental study; asymptotic normal test statistic; p-value mixture model; quasi-likelihood; weak dependence |
| Journal Title: | Statistical Applications in Genetics and Molecular Biology |
| Volume: | 6 |
| Issue: | 1 |
| ISSN: | 1544-6115 |
| Publisher: | The Berkeley Electronic Press |
| Date Published: | 2007-01-01 |
| Start Page: | 14 |
| Language: | English |
| PUBMED: | 17542776 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | --- - "Cited By (since 1996): 1" - "Export Date: 17 November 2011" - "Source: Scopus" |
