Outlier Detection and False Discovery Rates for Whole-Genome DNA Matching

作者：Jung‐Ying Tzeng, William Byerley, Bernie Devlin, Kathryn Roeder, Larry Wasserman · 发表于：Journal of the American Statistical Association · 年份：2003 · DOI：10.1198/016214503388619256 · 被引用次数：33 · 研究领域：Genetic Associations and Epidemiology、Bayesian Methods and Mixture Models、Gene expression and cancer classification

We define a statistic, called the matching statistic, for locating regions of the genome that exhibit excess similarity among cases when compared to controls. Such regions are reasonable candidates for harboring disease genes. We find the asymptotic distribution of the statistic while accounting for correlations among sampled individuals. We then use the Benjamini and Hochberg false discovery rate (FDR) method for multiple hypothesis testing to find regions of excess sharing. The p values for each region involve estimated nuisance parameters. Under appropriate conditions, we show that the FDR method based on p values and with estimated nuisance parameters asymptotically preserves the FDR property. Finally, we apply the method to a pilot study on schizophrenia.