Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

ABSTRACT:

Background

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data.

Results

In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray ex

SUBMITTER: Yao J 

PROVIDER: S-EPMC2459189 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature