The effects of normalization on the correlation structure of microarray data.

ABSTRACT:

Background

Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-statistics across genes. It is frequently assumed that dependence between genes (or tests) is sufficiently weak to justify the proposed methods of testing for differentially expressed genes. A potential impact of between-gene correlations on the performance of such methods has yet to be explored.

Results

The paper presents a systematic study of correlation between the t-statistics associated with different genes. We report the effects of four different normalization methods using a large set of microarray data on childhood leukemia in addition to several sets of simulated data. Our findings help deci

SUBMITTER: Qiu X 

PROVIDER: S-EPMC1156869 | biostudies-literature | 2005 May

REPOSITORIES: biostudies-literature