Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models

Daniel Gerhard; Melanie Bremer; Christian Ritz

doi:10.1111/biom.12124

Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models

Daniel Gerhard, Melanie Bremer, Christian Ritz

4 Citationer (Scopus)

Abstract

A unified modeling framework based on a set of nonlinear mixed models is proposed for flexible modeling of gene expression in real-time PCR experiments. Focus is on estimating the marginal or population-based derived parameters: cycle thresholds and ΔΔc(t), but retaining the conditional mixed model structure to adequately reflect the experimental design. Additionally, the calculation of model-average estimates allows incorporation of the model selection uncertainty. The methodology is applied for estimating the differential expression of a phosphate transporter gene OsPT6 in rice in comparison to a reference gene at several states after phosphate resupply. In a small simulation study the performance of the proposed method is evaluated and compared to a standard method.

Originalsprog	Engelsk
Tidsskrift	Biometrics
Vol/bind	70
Udgave nummer	1
Sider (fra-til)	247-254
Antal sider	8
ISSN	0006-341X
DOI	https://doi.org/10.1111/biom.12124
Status	Udgivet - mar. 2014

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10.1111/biom.12124

https://academic.oup.com/biometrics/article-pdf/70/1/247/53877923/biometrics_70_1_247.pdf

Citationsformater

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AB - A unified modeling framework based on a set of nonlinear mixed models is proposed for flexible modeling of gene expression in real-time PCR experiments. Focus is on estimating the marginal or population-based derived parameters: cycle thresholds and ΔΔc(t), but retaining the conditional mixed model structure to adequately reflect the experimental design. Additionally, the calculation of model-average estimates allows incorporation of the model selection uncertainty. The methodology is applied for estimating the differential expression of a phosphate transporter gene OsPT6 in rice in comparison to a reference gene at several states after phosphate resupply. In a small simulation study the performance of the proposed method is evaluated and compared to a standard method.

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Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models

Abstract

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