Incorporation of subject-level covariates in quantile normalization of miRNA data. (December 2015)

• Record Type: Journal Article
• Authors: Suyundikov, Anvar; Stevens, John; Corcoran, Christopher; Herrick, Jennifer; Wolff, Roger; Slattery, Martha
• Is Part Of: BMC genomics. Volume 16:Number 1(2015)
• Page Start: 1
• Page End: 10
• Publication Date: 2015-12
• Subjects: Normalization -- Differential expression -- miRNA; Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-015-2199-4
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Background Most 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. Results In 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. Conclusions When any subject-level covariates are available, the weighted quantile normalization method should be used over the conventional quantile normalization method.