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Fig. 4 | BMC Bioinformatics

Fig. 4

From: Application of the common base method to regression and analysis of covariance (ANCOVA) in qPCR experiments and subsequent relative expression calculation

Fig. 4

Results of regression analysis between concentration of hormone α1 and \( \Delta {C}_q^{(w)} \) where the two variables are (a) highly correlated (r2 = 0.962) and (b) correlated (r2 = 0.709). Plot of predicted relative expression ratios (\( \hat{R} \)) for (c) regression in A with 95% confidence interval (CI) and for (d) regression in B with 95% confidence interval (CI). (e). Plot of predicted relative expression ratios (\( \hat{R} \)) based on a linear regression between concentration of hormone α1 and \( {\Delta C}_q^{(w)} \) with 95% confidence interval (CI). Relative expression and CI in (c and d) are based on comparisons to average concentration of hormone α1 measured, while (e) compares to the largest concentration of hormone α1 measured. Vertical dotted lines indicate x0

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BMC Bioinformatics

ISSN: 1471-2105

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