• Computer Science
  • Published 2006

Clustering replicated microarray data via mixtures of random effects models for various covariance structures

@inproceedings{Ng2006ClusteringRM,
  title={Clustering replicated microarray data via mixtures of random effects models for various covariance structures},
  author={Shu Kay Ng and Geoffrey J. McLachlan and Richard Bean and Siu Wah Ng},
  year={2006}
}
A unified approach of mixed-effects model has been recently proposed for clustering correlated genes from different kinds of microarray experiments. With the so-called EM-based MIXture analysis WIth Random Effects (EMMIX-WIRE) model, both the gene-specific and tissue-specific random effects are taken into account in the (mixture) modelling of microarray data. In this paper, we focus on the applications of the EMMIX-WIRE model to the cluster analysis of microarray data with repeated measurements… CONTINUE READING