Spectral Quality Assessment for High-Throughput Tandem Mass Spectrometry Proteomics
Current techniques in tandem mass spectrometric analyses of cellular protein contents often produce thousands to tens of thousands of spectra per experiment. This study introduces a new algorithm, named SPEQUAL, which is aimed at automated tandem mass spectral quality assessment. The quality of a gi...
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Veröffentlicht in: | Omics (Larchmont, N.Y.) N.Y.), 2004-09, Vol.8 (3), p.255-265 |
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Zusammenfassung: | Current techniques in tandem mass spectrometric analyses of cellular protein contents often
produce thousands to tens of thousands of spectra per experiment. This study introduces
a new algorithm, named SPEQUAL, which is aimed at automated tandem mass spectral
quality assessment. The quality of a given spectrum can be evaluated from three basic components:
(i) charge state differentiation, (ii) total signal intensity, and (iii) signal-to-noise estimates.
The differentiation between single and multiple precursor charge states (i) provides
a binary score for a given spectrum. Components (ii) and (iii) provide partial scores which
are subsequently summarized and multiplied by the first score. SPEQUAL was applied to
over 10,000 data files derived from almost 3,000 tandem mass spectra, and the results (final
cumulative scores) were manually verified. SPEQUAL's performance was determined
to have high sensitivity and specificity and low error rates for both spectral quality estimates
in general and precursor charge state differentiation in particular. Each of the partial scores
is controlled by adjustable thresholds to fine-tune SPEQUAL's performance for different
analysis pipelines and instrumentation. This spectral quality assessment tool is intended to
act in an advisory role to the researcher, assisting in filtration of thousands of spectra typically
produced by high throughput tandem mass spectrometric proteome analyses. Lastly,
SPEQUAL was implemented as Java GUI-based and command-line-based interfaces freely
available for both academic and industrial researchers. |
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ISSN: | 1536-2310 1557-8100 1557-8100 |
DOI: | 10.1089/omi.2004.8.255 |