LinRegPCR was developed by Dr Jan Ruijter, a principle investigator in the department of Anatomy, Embryology and Physiology (Academic Medical Centre, Amsterdam, the Netherlands). The statistical analysis of his own research data led to the development of this widely used program called LinRegPCR
LinRegPCR is a program for the analysis quantitative PCR (qPCR) data based on PCR efficiency values derived from amplification curves. The program imports non-baseline corrected data, performs a baseline correction on each sample separately, determines a window-of-linearity and then uses linear regression analysis to determine the PCR efficiency per sample from the slope of the regression line. The mean PCR efficiency per amplicon is calculated. The fluorescence threshold is then set to determine the Cq value. The mean PCR efficiency per amplicon and the Cq value per sample are then used to calculate a starting concentration per sample, expressed in arbitrary fluorescence units.
Click here to download your FREE LinRegPCR program
- Ruijter et al. Fluorescent-increase kinetics of different fluorescent reporters used for qPCR depend on monitoring chemistry, targeted sequence, type of DNA input and PCR efficiency. Microchimica Acta 2014 (DOI 10.1007/s00604-013-1155-8)
- Ruijter et al. Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications. Methods 59: 32-46, 2013
- Tuomi et al. Bias in the Cq value observed with hydrolysis probe based quantitative PCR can be corrected with the estimated PCR efficiency value. Methods 50: 313-322, 2010
- Ruijter et al. Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Research 37: e45, 2009
- Karlen et al. Statistical significance of quantitative PCR. BMC Bioinformatics 8: 131, 2007
- Cikos et al. Relative quantification of mRNA: comparison of methods currently used for real-time PCR data analysis. BMC Mol Biol 8: 113, 2007
- Ramakers et al. Assumption-free analysis of quantitative real-time PCR data. Neurosci Letters 339: 62-66, 2003
Dr Jan Ruijter recently developed another program called Factor-qPCR. This program removes “multiplicative between-run variation” that occurs when a quantitative PCR experiment includes multiple plates to accommodate all samples, targets and replications. These replicate runs show similar proportional differences between experimental conditions, but different absolute values, even though the measurements are presumably carried out under identical circumstances. In most cases, between-session variation is multiplicative and can, therefore, be removed by division of the data in each session with a session-specific correction factor.
Click here to download your FREE Factor-qPCR program
- Ruijter JM, Ruiz Villalba A, Hellemans J, Untergasser A, van den Hoff MJB. Removal of between-run variation in a multi-plate qPCR experiment. Biomolecular Detection and Quantification In Press, 2015.
- Ruijter JM, Thygesen HH, Schoneveld JLM, Das A, Berkhout B, and Lamers WH. Factor correction as a tool to eliminate between-session variation in replicate experiments: application to molecular biology and retrovirology. Retrovirology 3:2, 2006.
- Lefever S, Hellemans J, Pattyn F, Przybylski DR, Taylor C, Geurts R, Untergasser A, Vandesompele J; RDML consortium.. RDML: structured language and reporting guidelines for real-time quantitative PCR data.
- Ruijter JM, Lefever S, Anckaert J, Hellemans J, Pfaffl MW, Benes V, Bustin SA, Vandesompele J, Untergasser A; RDML consortium.. RDML-Ninja and RDMLdb for standardized exchange of qPCR data.
Introducing “Mic” your personal qPCR Cycler
Its FAST, ACCURATE, COMPACT and SCALABLE.
Its the FIRST qPCR instrument to follow the LinRegPCR principles for the analysis of its qPCR data.
And its Designed and Manufactured by Bio Molecular System, an Australian company founded by the leading innovators of the former Corbett Research Life Sciences company.
Click here to meet Mic