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

ABSTRACT: 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.

SUBMITTER: Garcia B

PROVIDER: S-EPMC4100614 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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

Garcia Benjamin B Walter Nicholas D ND Dolganov Gregory G Coram Marc M Davis J Lucian JL Schoolnik Gary K GK Strong Michael M

Analytical biochemistry 20140426

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 me ...[more]

PMID: 24780223

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