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Updated: Mar 29, 2026

Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR
Published on: January 22, 2014
Incorporation of subject-level covariates in quantile normalization of miRNA data
Anvar Suyundikov1,2, John R Stevens3, Christopher Corcoran4
1Department of Mathematics and Statistics, Utah State University, 3900 Old Main Hill, Logan, 84322-3900, UT, U.S.A. asu@biostatsolutions.com.
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.
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