Automated validation of polymerase chain reactions using amplicon melting curves
Tobias Mann, Richard Humbert, John Stamatoyannopolous and William Stafford Noble
The Computational Systems Bioinformatics Conference, Stanford, CA, August 8-11, 2005. pp. 377-385.
PCR is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for measurement of transcription, analysis of DNA-protein interactions via chromatin immunoprecipitation, determination of DNA copy numbers, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses or for manufacture of conventional genomic DNA microarrays is the current requirement for manual validation of individual PCR reactions to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCR reactions---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 PCR reactions from each of 1,728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCR reactions 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.