uAnalyze: Web-Based High-Resolution DNA Melting Analysis with Comparison to Thermodynamic Predictions
Issue No. 06 - Nov.-Dec. (2012 vol. 9)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2012.112
Z. L. Dwight , Dept. of Pathology, Univ. of Utah, Salt Lake City, UT, USA
R. Palais , Dept. of Math., Utah Valley Univ., Orem, UT, USA
C. T. Wittwer , Dept. of Pathology, Univ. of Utah, Salt Lake City, UT, USA
uAnalyzeSM is a web-based tool for analyzing high-resolution melting data of PCR products. PCR product sequence is input by the user and recursive nearest neighbor thermodynamic calculations used to predict a melting curve similar to uMELT (http://www.dna.utah.edu/umelt/umelt.html). Unprocessed melting data are input directly from LightScanner-96, LS32, or HR-1 data files or via a generic format for other instruments. A fluorescence discriminator identifies low intensity samples to prevent analysis of data that cannot be adequately normalized. Temperature regions that define fluorescence background are initialized by prediction and optionally adjusted by the user. Background is removed either as an exponential or by linear baseline extrapolation. The precision or, “curve spread,” of experimental melting curves is quantified as the average of the maximum helicity difference of all curve pairs. Melting curve accuracy is quantified as the area or “2D offset” between the average experimental and predicted melting curves. Optional temperature overlay (temperature shifting) is provided to focus on curve shape. Using 14 amplicons of CYBB, the mean +/ - standard deviation of the difference between experimental and predicted fluorescence at 50 percent helicity was -0.04 + / -0.48°C. uAnalyze requires Flash, is not browser specific and can be accessed at http://www.dna.utah.edu/uv/uanalyze.html.
Computational biology, Bioinformatics
Z. L. Dwight, R. Palais and C. T. Wittwer, "uAnalyze: Web-Based High-Resolution DNA Melting Analysis with Comparison to Thermodynamic Predictions," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 6, pp. 1805-1811, 2013.