A minimum variance method for genome-wide data-driven normalization of quantitative real-time polymerase chain reaction expression data.

Anal Biochem

Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, CO 80206, USA; Computational Bioscience Program, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA. Electronic address:

Published: August 2014

Advances in multiplex qRT-PCR have enabled increasingly accurate and robust quantification of RNA, even at lower concentrations, facilitating RNA expression profiling in clinical and environmental samples. Here we describe a data-driven qRT-PCR normalization method, the minimum variance method, and evaluate it on clinically derived Mycobacterium tuberculosis samples with variable transcript detection percentages. For moderate to significant amounts of nondetection (∼50%), our minimum variance method consistently produces the lowest false discovery rates compared to commonly used data-driven normalization methods.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4100614PMC
http://dx.doi.org/10.1016/j.ab.2014.04.021DOI Listing

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