Objectives: To enable analysis and comparisons of different relative quantitation experiments, a web-browser application called Harbin was created that uses a quantile-based scoring system for the comparison of samples at different time points and between experiments.
Results: Harbin uses the standard curve method for relative quantitation to calculate concentration ratios (CRs). To evaluate if different datasets can be combined the Harbin quantile bootstrap test is proposed. This test is more sensitive in detecting distributional differences between data sets than the Kolmogorov-Smirnov test. The utility of the test is demonstrated in a comparison of three grapevine leafroll associated virus 3 (GLRaV-3) RT-qPCR data sets.
Conclusions: The quantile-based scoring system of CRs will enable the monitoring of virus titre or gene expression over different time points and be useful in other genomic applications where the combining of data sets are required.
Keywords: Bootstrap; Concentration ratios; GLRaV-3; Genetic variants; Harbin; Location-scale-shape problem; Quantile-based scoring; RT-qPCR.