期刊
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
卷 67, 期 -, 页码 411-426出版社
WILEY
DOI: 10.1111/j.1467-9868.2005.00509.x
关键词
false discovery rate; microarrays; multiple comparisons; single-nucleotide polymorphisms; step-down
In high throughput genomic work, a very large number d of hypotheses are tested based on n << d data samples. The large number of tests necessitates an adjustment for false discoveries in which a true null hypothesis was rejected. The expected number of false discoveries is easy to obtain. Dependences between the hypothesis tests greatly affect the variance of the number of false discoveries. Assuming that the tests are independent gives an inadequate variance formula. The paper presents a variance formula that takes account of the correlations between test statistics. That formula involves O(d(2)) correlations, and so a naive implementation has cost O(nd(2)). A method based on sampling pairs of tests allows the variance to be approximated at a cost that is independent of d.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据