Dr. Jan M. Ruijter trained as a medical biologist and worked in endocrinology, neurobiology, ophthalmology and embryology. He recently retired from his position as principle investigator in the department of Medical Biology (Academic Medical Centre, Amsterdam, the Netherlands) where he was heading a research group studying the relation between gene expression and the development of the heart with molecular, image analysis and 3D-reconstruction techniques.

The statistical analysis of research data resulted in the development of LinRegPCR, a program for the analysis of quantitative PCR data based on PCR efficiency values derived from amplification curves, and Factor-qPCR, a program to remove between-plate variation in a multi-plate qPCR experiment (http://LinRegPCR.nl). A survey of amplification curve analysis programs showed that LinRegPCR is among the most sensitive and reproducible methods. LinRegPCR imports raw fluorescence data, performs baseline correction and reports efficiency-corrected target quantities based on the mean PCR efficiency per target; its compatibility with Excel and RDML places the program in a pipeline between the qPCR apparatus and final statistical analysis.

​Jan is still involved in advanced qPCR courses and currently working on papers on PCR artefacts and data analysis. 

​Selected qPCR Bibliography:
1.   Ramakers, C., Ruijter, J.M., Lekanne Deprez, R.H. and Moorman, A.F.M. (2003) Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci.Lett., 339, 62-66.
2.   Ruijter, J.M., Ramakers, C., Hoogaars, W.M., Karlen, Y., Bakker, O., van den Hoff, M.J. and Moorman, A.F. (2009) Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res., 37, e45.
3.   Ruijter, J.M., Pfaffl, M.W., Zhao, S., Spiess, A.N., Boggy, G., Blom, J., Rutledge, R.G., Sisti, D., Lievens, A., De Preter, K. et al. (2013) Evaluation of qPCR curve analysis methods for reliable biomarker discovery: Bias, resolution, precision, and implications. Methods, 59, 32-46.
4.   Ruijter, J.M., Lorenz, P., Tuomi, J.M., Hecker, M. and van den Hoff, M.J. (2014) Fluorescent-increase kinetics of different fluorescent reporters used for qPCR depend on monitoring chemistry, targeted sequence, type of DNA input and PCR efficiency. Mikrochim.Acta, 181, 1689-1696.
5. Ruijter, J.M, A. Ruiz-Villalba, J. Hellemans and A. Untergasser (2015). Removal of between-run variation in a multi-plate qPCR experiment.  Biomol Detect Quantif 5. 10-14.
6. De Ronde, M.W.J., J.M. Ruijter, D. Lanfeard, A. Bayes-Genise, M.G.M. Kok, E.E. Creemers, Y.M. Pinto, S-J. and Pinto-Sietsma (2017). Practical data handling pipeline improves performance of qPCR-based circulating miRNA measurements. RNA 23. 811-821.
7. Ruiz-Villalba A, A. Mattiotti, Q.D. Gunst, S. Cano-Ballesteros, M.J. van den Hoff, and J.M. Ruijter (2017). Reference genes for gene expression studies in the mouse heart. Scientific Reports 7. e24.
8. Ruiz-Villalba, A., E. van Pelt-Verkuil, Q.D. Gunst, J.M Ruijter, and M.J. van den Hoff (2017) Amplification of nonspecific products in quantitative polymerase chain reactions (qPCR). Biomol Detect Quantif 14. 7-18.