Journal
JOURNAL OF APPLIED STATISTICS
Volume 45, Issue 2, Pages 306-319Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/02664763.2016.1276890
Keywords
Real-time PCR data; in silico; gene expression; statistical analysis; SAS procedures
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Funding
- Agricultural Faculty of Ferdowsi University of Mashhad, Iran [368P]
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Real-time polymerase chain reaction (PCR) is reliable quantitative technique in gene expression studies. The statistical analysis of real-time PCR data is quite crucial for results analysis and explanation. The statistical procedures of analyzing real-time PCR data try to determine the slope of regression line and calculate the reaction efficiency. Applications of mathematical functions have been used to calculate the target gene relative to the reference gene(s). Moreover, these statistical techniques compare C-t (threshold cycle) numbers between control and treatments group. There are many different procedures in SAS for real-time PCR data evaluation. In this study, the efficiency of calibrated model and delta delta C-t model have been statistically tested and explained. Several methods were tested to compare control with treatment means of C-t. The methods tested included t-test (parametric test), Wilcoxon test (non-parametric test) and multiple regression. Results showed that applied methods led to similar results and no significant difference was observed between results of gene expression measurement by the relative method.
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