Incorporation of subject-level covariates in quantile normalization of miRNA data.

Abstract

BackgroundMost currently-used normalization methods for miRNA array data are based on methods developed for mRNA arrays despite fundamental differences between the data characteristics. The application of conventional quantile normalization can mask important expression differences by ignoring demographic and environmental factors. We present a generalization of the conventional quantile normalization method, making use of available subject-level covariates in a colorectal cancer study.ResultsIn simulation, our weighted quantile normalization method is shown to increase statistical power by as much as 10 % when relevant subject-level covariates are available. In application to the colorectal cancer study, this increase in power is also observed, and previously-reported dysregulated miRNAs are rediscovered.ConclusionsWhen any subject-level covariates are available, the weighted quantile normalization method should be used over the conventional quantile normalization method.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2199-4) contains supplementary material, which is available to authorized users.