Web-based LinRegPCR: application for the visualization and analysis of (RT)-qPCR amplification and melting data

Andreas Untergasser,Jan M Ruijter,Vladimir Benes,Maurice J B Van Den Hoff

doi:10.1186/s12859-021-04306-1

Andreas Untergasser, Jan M Ruijter + Show 2 more

Open Access

https://doi.org/10.1186/s12859-021-04306-1

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Abstract

BackgroundThe analyses of amplification and melting curves have been shown to provide valuable information on the quality of the individual reactions in quantitative PCR (qPCR) experiments and to result in more reliable and reproducible quantitative results.ImplementationThe main steps in the amplification curve analysis are (1) a unique baseline subtraction, not using the ground phase cycles, (2) PCR efficiency determination from the exponential phase of the individual reactions, (3) setting a common quantification threshold and (4) calculation of the efficiency-corrected target quantity with the common threshold, efficiency per assay and Cq per reaction. The melting curve analysis encompasses smoothing of the observed fluorescence data, normalization to remove product-independent fluorescence loss, peak calling and assessment of the correct peak by comparing its melting temperature with the known melting temperature of the intended amplification product.ResultsThe LinRegPCR web application provides visualization and analysis of a single qPCR run. The user interface displays the analysis results on the amplification curve analysis and melting curve analysis in tables and graphs in which deviant reactions are highlighted. The annotated results in the tables can be exported for calculation of gene-expression ratios, fold-change between experimental conditions and further statistical analysis. Web-based LinRegPCR addresses two types of users, wet-lab scientists analyzing the amplification and melting curves of their own qPCR experiments and bioinformaticians creating pipelines for analysis of series of qPCR experiments by splitting its functionality into a stand-alone back-end RDML (Real-time PCR Data Markup Language) Python library and several companion applications for data visualization, analysis and interactive access. The use of the RDML data standard enables machine independent storage and exchange of qPCR data and the RDML-Tools assist with the import of qPCR data from the files exported by the qPCR instrument.ConclusionsThe combined implementation of these analyses in the newly developed web-based LinRegPCR (https://www.gear-genomics.com/rdml-tools/) is platform independent and much faster than the original Windows-based versions of the LinRegPCR program. Moreover, web-based LinRegPCR includes a novel statistical outlier detection and the combination of amplification and melting curve analyses allows direct validation of the amplification product and reporting of reactions that amplify artefacts.

Highlights

The analyses of amplification and melting curves have been shown to provide valuable information on the quality of the individual reactions in quantitative Polymerase chain reaction (PCR) experiments and to result in more reliable and reproducible quantitative results.Implementation: The main steps in the amplification curve analysis are (1) a unique baseline subtraction, not using the ground phase cycles, (2) PCR efficiency determination from the exponential phase of the individual reactions, (3) setting a common quantification threshold and (4) calculation of the efficiency-corrected target quantity with the common threshold, efficiency per assay and Quantification cycle (Cq) per reaction
Real-time PCR data markup language (RDML) is available free of charge, not all quantitative PCR (qPCR) machines support the export to RDML files
For analysis of fluorescence data generated by these machines, the user needs to create an RDML file from the text files or spreadsheets exported from their qPCR machine

Summary

Introduction

The analyses of amplification and melting curves have been shown to provide valuable information on the quality of the individual reactions in quantitative PCR (qPCR) experiments and to result in more reliable and reproducible quantitative results.Implementation: The main steps in the amplification curve analysis are (1) a unique baseline subtraction, not using the ground phase cycles, (2) PCR efficiency determination from the exponential phase of the individual reactions, (3) setting a common quantification threshold and (4) calculation of the efficiency-corrected target quantity with the common threshold, efficiency per assay and Cq per reaction. The qPCR machine subtracts a baseline fluorescence, sets a quantification threshold and reports the Cq value, which is the number of cycles required to reach that threshold [2]. More advanced users derive the PCR efficiency from a standard curve [4] and calculate efficiency-corrected outcomes for their qPCR experiments [5]. Several methods to analyse amplification curves were proposed [6,7,8,9,10,11,12,13] These methods report a C q value and derive an efficiency value and some quality measures from each amplification reaction. A comparison of these methods showed that the amplification curve analysis performed by LinRegPCR achieved qPCR results with the lowest variation and highest reproducibility [14]

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Discussion

Conclusion