title: Analysis and interpretation of data from real-time PCR trace detection methods using quantitation of GM soya as a model system.
abstract: Recent years have seen an increased interest in DNA trace detection methods involved in many areas of bioanalytical research, such as quantitation of genetically modified (GM) ingredients in food products. There is little in the way of standardisation of data handling from these methods, and the data generated needs to be analysed appropriately if the results are to be interpreted correctly. This paper describes particular aspects of real-time PCR trace detection methods in order to increase the understanding of data generated using this bioanalytical technique. Using the specific example of GM soya detection and quantitation, it focuses on the production of calibration curves based on the mean and individual data values, the interpretation of correlation coefficients, regression techniques, and discusses suitable data analysis arising from simple and more complex experimental designs following transformation. By using the approaches outlined in this paper, more accurate analysis of data from real-time PCR and GM trace detection methods could be achieved.
authors.affiliation: BioAnalytical Innovation Team, LGC Limited, Queens Road, Teddington, Middlesex, TW11 OLY, UK. Malcolm.Burns@lgc.co.uk
authors.forename: Malcolm J
authors.initials: MJ
authors.lastname: Burns
authors.forename: Hernan
authors.initials: H
authors.lastname: Valdivia
authors.forename: Neil
authors.initials: N
authors.lastname: Harris
mesh_terms: D002138:Calibration; D003627:Data Interpretation, Statistical; D005504:Food Analysis / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D030841:Food, Genetically Modified; D012044:Regression Analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods*; D013025:Glycine max / Q000737:chemistry* / Q000235:genetics