Statistical analysis of real-time PCR data.

ABSTRACT:

Background

Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.

Results

In the first approach, a multiple regression analysis model was developed to derive DeltaDeltaCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was

SUBMITTER: Yuan JS 

PROVIDER: S-EPMC1395339 | biostudies-literature | 2006 Feb

REPOSITORIES: biostudies-literature