Dr Jan M Ruijter - Academic Medical Center, the Netherlands

Dr Jan M Ruijter - Academic Medical Center, the Netherlands

Location: 
Seminar Room 1
Start Time: 
Thu, 03/09/2015 - 11:00am
End Time: 
Thu, 03/09/2015 - 12:00pm

​Analysis of quantitative PCR data: from raw fluorescence to between-plate correction

​RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In the analysis of qPCR data, the PCR efficiency is mostly assumed to be 2 (100% efficient) which can lead to strongly biased results especially when the PCR efficiencies of target and reference genes are not equal. In this presentation, the principle of the analysis of qPCR data, the reasons for amplification curve analysis, and the performance of the published analysis methods will be discussed.
The results of a comparison of analysis methods show that the use of the target specific PCR efficiency values leads to less variable results and thus to more powerful qPCR assays. The strength of amplification curve analysis will be illustrated with data sets in which target concentration and primer concentration were varied to study the effect on amplification efficiency and occurrence of PCR artefacts. Because large scale qPCR analyses are often not be restricted to 1 plate, the removal of such between-plate variation will be addressed. The implementation of between-plate correction, Factor-qPCR, completes the analysis pipeline from raw data through LinRegPCR into normalization and statistics using qbase-plus.
Jan M Ruijter trained as a medical biologist and worked in endocrinology, neurobiology, ophthalmology and embryology. He is currently appointed as principle investigator in the department of Anatomy, Embryology & Physiology (Academic Medical Centre, Amsterdam, the Netherlands) where he is 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 the LinRegPCR, a program for the analysis quantitative PCR data based on PCR efficiency values derived from amplification curves, and Factor-qPCR, a program to remove between-plate variation in multi-plate qPCR experiments.