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Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Toprak UH, Gillet LC, Maiolica A, Navarro P, Leitner A, Aebersold R - Mol. Cell Proteomics (2014)

Bottom Line: In both cases, confidence in peptide identification is directly related to the quality of spectral matches.Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure.The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;

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Response of (A) dot product, (B) spectral correlation, and (C) normalized spectral contrast angle to increasing perturbations. The violin plots combine the kernel density estimation of the score distributions with the statistical features shown by the overlaid box plots. The blue tails denote individual outlier scores at each perturbation level.
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Figure 1: Response of (A) dot product, (B) spectral correlation, and (C) normalized spectral contrast angle to increasing perturbations. The violin plots combine the kernel density estimation of the score distributions with the statistical features shown by the overlaid box plots. The blue tails denote individual outlier scores at each perturbation level.

Mentions: Fig. 1 shows the response of the three most commonly used similarity measures, dot product, spectral correlation, and normalized spectral contrast angle, toward the systematic perturbations of our benchmark spectral library. The results indicate that the normalized spectral contrast angle shows the best performance among the compared similarity measures, with a consistent decreasing trend over the whole range of perturbation strength and with small variations and minimal overlap for each perturbation step (Fig. 1C). In comparison, the dot product displayed a relatively weak response to stochastic perturbations (Fig. 1A), reporting scores below 0.8 only for the strongest perturbation levels (80–100%). Spectral correlation, on the other hand, generated a large number of low scores even for low perturbation levels, as highlighted by the prevalence of outliers (Fig. 1B). Furthermore, its score distribution presented important overlaps between adjacent spectral perturbation levels. The performance assessment for two additional geometric distance measures, Bray-Curtis distance and Euclidean distance, using the same benchmarked perturbation spectra set approach can be seen in the supplemental material (supplemental Fig. S5). Both measures showed an overall good performance. Based on these results, we decided to use the normalized spectral contrast angle as the similarity measure of choice for the remainder of this study.


Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Toprak UH, Gillet LC, Maiolica A, Navarro P, Leitner A, Aebersold R - Mol. Cell Proteomics (2014)

Response of (A) dot product, (B) spectral correlation, and (C) normalized spectral contrast angle to increasing perturbations. The violin plots combine the kernel density estimation of the score distributions with the statistical features shown by the overlaid box plots. The blue tails denote individual outlier scores at each perturbation level.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4125737&req=5

Figure 1: Response of (A) dot product, (B) spectral correlation, and (C) normalized spectral contrast angle to increasing perturbations. The violin plots combine the kernel density estimation of the score distributions with the statistical features shown by the overlaid box plots. The blue tails denote individual outlier scores at each perturbation level.
Mentions: Fig. 1 shows the response of the three most commonly used similarity measures, dot product, spectral correlation, and normalized spectral contrast angle, toward the systematic perturbations of our benchmark spectral library. The results indicate that the normalized spectral contrast angle shows the best performance among the compared similarity measures, with a consistent decreasing trend over the whole range of perturbation strength and with small variations and minimal overlap for each perturbation step (Fig. 1C). In comparison, the dot product displayed a relatively weak response to stochastic perturbations (Fig. 1A), reporting scores below 0.8 only for the strongest perturbation levels (80–100%). Spectral correlation, on the other hand, generated a large number of low scores even for low perturbation levels, as highlighted by the prevalence of outliers (Fig. 1B). Furthermore, its score distribution presented important overlaps between adjacent spectral perturbation levels. The performance assessment for two additional geometric distance measures, Bray-Curtis distance and Euclidean distance, using the same benchmarked perturbation spectra set approach can be seen in the supplemental material (supplemental Fig. S5). Both measures showed an overall good performance. Based on these results, we decided to use the normalized spectral contrast angle as the similarity measure of choice for the remainder of this study.

Bottom Line: In both cases, confidence in peptide identification is directly related to the quality of spectral matches.Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure.The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland;

Show MeSH