文章基本信息

标题：Independent filtering increases detection power for high-throughput experiments
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作者：Richard Bourgon ; Robert Gentleman ; Wolfgang Huber 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2010
卷号：107
期号：21
页码：9546-9551
DOI：10.1073/pnas.0914005107
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by a criterion independent of the test statistic, and then only tests variables which pass the filter, can provide higher power. We show that use of some filter/test statistics pairs presented in the literature may, however, lead to loss of type I error control. We describe other pairs which avoid this problem. In an application to microarray data, we found that gene-by-gene filtering by overall variance followed by a t-test increased the number of discoveries by 50%. We also show that this particular statistic pair induces a lower bound on fold-change among the set of discoveries. Independent filtering--using filter/test pairs that are independent under the null hypothesis but correlated under the alternative--is a general approach that can substantially increase the efficiency of experiments.
关键词：gene expression ; multiple testing