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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
