Automated validation of polymerase chain reactions using amplicon melting curves

Tobias Mann, Richard Humbert, John Stamatoyannopolous and William Stafford Noble

Journal of Bioinformatics and Computational Biology. 22(14):350--358, 2006.


The polymerase chain reaction (PCR) is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCRs to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCRs -- a time-consuming and costly process. Here we describe a robust computational solution to this fundamental problem. Using a training set of 10,080 reactions comprising multiple quantitative PCRs from each of 1728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCRs with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications.