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Jens Bjorkman 1, 1TATAA Biocenter, Sweden |
Abstract
qPCR is today a mature and most established method. Still it is easy to neglect the underlying factors that may compromise the results. With an easy-to-use highly automated qPCR instrument in every lab, scientist can (if they choose) generate data with mini- mum focus on the pre-qPCR parameters that may have significant impact on the data. It is not difficult to produce Cq-values, but how do we know that they truly reflect the amount of target that was actually present in the original sample or even in vivo? As described in the MIQE guidelines proper controls should be included in order to identify and in some cases correct for the bias caused by pre- analytical parameters and technical variation. I will describe quality control measures to test for degradation of RNA, RT and PCR inhibi- tion, genomic DNA background, and provide means to compensate for interplate variation to perform high quality quantitative PCR measurements.
http://dx.doi.org/10.1016/j.bdq.2017.02.072
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