Stouffer's test in a large scale simultaneous hypothesis testing.

ABSTRACT: In microarray data analysis, we are often required to combine several dependent partial test results. To overcome this, many suggestions have been made in previous literature; Tippett's test and Fisher's omnibus test are most popular. Both tests have known null distributions when the partial tests are independent. However, for dependent tests, their (even, asymptotic) null distributions are unknown and additional numerical procedures are required. In this paper, we revisited Stouffer's test based on z-scores and showed its advantage over the two aforementioned methods in the analysis of large-scale microarray data. The combined statistic in Stouffer's test has a normal distribution with mean 0 from the normality of the z-scores. Its variance can be estimated from the scores of genes in the

SUBMITTER: Kim SC 

PROVIDER: S-EPMC3653960 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature