Assessment and performance of VSN-Inv normalization on the NCI-60 microRNA expression profiles.

摘要

Multiple normalization methods have been proposed for the analysis of microRNA microarray expression profiles but there is no consensus method. One of the more robust methods, quantile normalization, is commonly used in transcript (mRNA) studies and was therefore used for normalizing the first microRNA expression profiles of the NCI-60 cell panel, published in 2007. In this study the appropriateness of VSN-Inv, a recently proposed alternative normalization method, to the NCI-60 dataset is verified. VSN-Inv normalization results in much increased inter-sample correlations among control groups, and significantly higher intra-chip correlations of duplicate probes, versus quantile and no normalization. Furthermore, VSN-Inv normalization was found to have favorable performance for hierarchical clustering and discovery of miRNA-mRNA interactions, and a lower misclassification rate for predictive analysis based on tissue of origin when using log transformed data (median 0.19, best 0.12).