MOTIVATION: Reproducibility, a cornerstone of research, requires defined data formats, which include the setup and output of experiments. The real-time PCR data markup language (RDML) is a recommended standard of the minimum information for publication of quantitative real-time PCR experiments guidelines. Despite the popularity of the RDML format for analysis of quantitative PCR data, handling of RDML files is not yet widely supported in all PCR curve analysis softwares. RESULTS: This study describes the open-source RDML package for the statistical computing language R. RDML is compatible with RDML versions ≤ 1.2 and provides functionality to (i) import RDML data; (ii) extract sample information (e.g. targets and concentration); (iii) transform data to various formats of the R environment; (iv) generate human-readable run summaries; and (v) to create RDML files from user data. In addition, RDML offers a graphical user interface to read, edit and create RDML files. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/package=RDML. rdmlEdit server http://shtest.evrogen.net/rdmlEdit/. Documentation: http://kablag.github.io/RDML/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: The qpcR library is an add-on to the free R statistical environment performing sigmoidal model selection in real-time quantitative polymerase chain reaction (PCR) data analysis. Additionally, the package implements the most commonly used algorithms for real-time PCR data analysis and is capable of extensive statistical comparison for the selection and evaluation of the different models based on several measures of goodness of fit. AVAILABILITY: www.dr-spiess.de/qpcR.html. SUPPLEMENTARY INFORMATION: Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under 'Supplemental Data'.

BACKGROUND: Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data. RESULTS: The four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods. CONCLUSION: The five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage.