Chromatographic Alignment of ESI-LC-MS Proteomics Data Sets by Ordered Bijective Interpolated Warping
Mass spectrometry proteomics typically relies upon analyzing outcomes of single analyses; however, comparing raw data across multiple experiments should enhance both peptide/protein identification and quantitation. In the absence of convincing tandem MS identifications, comparing peptide quantities...
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Veröffentlicht in: | Analytical chemistry (Washington) 2006-09, Vol.78 (17), p.6140-6152 |
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Sprache: | eng |
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Zusammenfassung: | Mass spectrometry proteomics typically relies upon analyzing outcomes of single analyses; however, comparing raw data across multiple experiments should enhance both peptide/protein identification and quantitation. In the absence of convincing tandem MS identifications, comparing peptide quantities between experiments (or fractions) requires the chromatographic alignment of MS signals. An extension of dynamic time warping (DTW), termed ordered bijective interpolated warping (OBI-Warp), is presented and used to align a variety of electrospray ionization liquid chromatography mass spectrometry (ESI-LC-MS) proteomics data sets. An algorithm to produce a bijective (one-to-one) function from DTW output is coupled with piecewise cubic hermite interpolation to produce a smooth warping function. Data sets were chosen to represent a broad selection of ESI-LC-MS alignment cases. High confidence, overlapping tandem mass spectra are used as standards to optimize and compare alignment parameters. We determine that Pearson's correlation coefficient as a measure of spectra similarity outperforms covariance, dot product, and Euclidean distance in its ability to produce correct alignments with optimal and suboptimal alignment parameters. We demonstrate the importance of penalizing gaps for best alignments. Using optimized parameters, we show that OBI-Warp produces alignments consistent with time standards across these data sets. The source and executables are released under MIT style license at http://obi-warp.sourceforge.net/. |
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ISSN: | 0003-2700 1520-6882 |
DOI: | 10.1021/ac0605344 |