On the risk of false positive identification using multiple ion monitoring in qualitative mass spectrometry: Large-scale intercomparisons with a comprehensive mass spectral library

  • Stephen E. SteinEmail author
  • David N. Heller


Analysts involved in qualitative mass spectrometry have long debated the minimum data requirements for demonstrating that signals from an unknown sample are identical to those from a known compound. Often this process is carried out by comparing a few selected ions acquired by multiple ion monitoring (MIM), with due allowance for expected variability in response. In a few past experiments with electron-ionization mass spectrometry (EI-MS), the number of ions selected and the allowable variability in relative abundance were tested by comparing one spectrum against a library of mass spectra, where library spectra served to represent potential false positive signals in an analysis. We extended these experiments by carrying out large-scale intercomparisons between thousands of spectra and a library of one hundred thousand EI mass spectra. The results were analyzed to gain insights into the identification confidence associated with various numbers of selected ions. A new parameter was investigated for the first time, to take into account that a library spectrum with a different base peak than the search spectrum may still cause a false positive identification. The influence of peak correlation among the specific ions in all the library mass spectra was also studied. Our computations showed that (1) false positive identifications can result from similar compounds, or low-abundance peaks in unrelated compounds if the method calls for detection at very low levels; (2) a MIM method’s identification confidence improves in a roughly continuous manner as more ions are monitored, about one order of magnitude for each additional ion selected; (3) full scan spectra still represent the best alternative, if instrument sensitivity is adequate. The use of large scale intercomparisons with a comprehensive library is the only way to provide direct evidence in support of these conclusions, which otherwise depend on the judgment and experience of individual analysts. There are implications for residue chemists who would rely on standardized confirmation criteria to assess the validity of a given confirmatory method. For example, standardized confirmation criteria should not be used in the absence of interference testing and rational selection of diagnostic ions.


  1. 1.
    Auslos, P.; Clifton, C. L.; Lias, W. G.; Mikaya, A. I.; Stein, S. E.; Tchekhovskoi, D. V.; Sparkman, O. D.; Zaikin, V.; Zhu, D. The critical evaluation of a comprehensive mass spectral library. J. Am. Soc. Mass Spectrom. 1999, 10, 287–299.CrossRefGoogle Scholar
  2. 2.(a)
    Stein, S. E.; Scott, D. R. Optimization and testing of mass spectral search algorithms for compound identification. J. Am. Soc. Mass Spectrom. 1994, 5, 859–866;CrossRefGoogle Scholar
  3. 2.(b)
    Stein, S. E. Probabilities of correct identification from results of MS library searching. J. Am. Soc. Mass Spectrom 1994, 5, 316–323, and references therein.CrossRefGoogle Scholar
  4. 3.
    Cargile, B. J.; Bundy, J. L.; Stephenson, J. L. Potential for false positive identifications from large databases through tandem mass spectrometry. J. Proteome Res. 2004, 5, 1082–1085.CrossRefGoogle Scholar
  5. 4.
    Vessman, J.; Stefan, R. I.; Van Staden, J. F.; Danzer, K.; Lindner, W.; Burns, D. T.; Fajgelj, A.; Muller, H. Selectivity in Analytical Chemistry. Pure Appl. Chem. 2001, 73, 1381–1386.CrossRefGoogle Scholar
  6. 5.
    Van Ginkel, L. A.; Stephany, R. W. Experimental chemometrics, an alternative way for estimating overall reliability; Proceedings of the Euroresidues II Conference on Residues of Veterinary Drugs in Food Haagsma, N., Ed.; Veldhoven, Netherlands, May, 1993; pp 303–307.Google Scholar
  7. 6.
    Sphon, J. A. Use of mass spectrometry for confirmation of animal drug residues. J. Assoc. Off. Anal. Chem. 1978, 61, 1247–1252.Google Scholar
  8. 7.
    Baldwin, R.; Bethem, R. A.; Boyd, R.; Budde, W. L.; Cairns, T.; Gibbons, R. D.; Henion, J. D.; Kaiser, M. A.; Lewis, D. L.; Matusik, J. E.; Sphon, J. A.; Stephany, R. W.; Trubey, R. K. Report on 1996 ASMS Fall Workshop: Limits to confirmation, quantitation, and detection. J. Am. Soc. Mass Spectrom. 1997, 8, 1180–1190.CrossRefGoogle Scholar
  9. 8.
    Webb, K.; Sargent, M. The reliability of mass spectrometry for identification purposes. VAM Bulletin of the Laboratory of the Government Chemist: Teddington, UK: 2000, 22, 12–14.Google Scholar
  10. 9.
    Bristow, A. W. T.; Webb, W. S.; Lubben, A. T.; Halket, J. Reproducible product-ion tandem mass spectra on various liquid chromatography/mass spectrometry instruments for the development of spectral libraries. Rapid Commun. Mass Spectrom. 2004, 18, 1447–1454.CrossRefGoogle Scholar
  11. 10.
    Hough, J. M.; Haney, C. A.; Voyksner, R. D.; Bereman, R. D. Evaluation of electrospray transport CID for the generation of searchable libraries. Anal. Chem. 2000, 72, 2265–2270.CrossRefGoogle Scholar
  12. 11.
    Josephs, J. L.; Sanders, M. Creation and comparison of MS/MS spectral libraries using quadrupole ion trap and triple-quadrupole mass spectrometers. Rapid Commun. Mass Spectrom. 2004, 18, 743–759.CrossRefGoogle Scholar
  13. 12.
    FDA Center for Veterinary Medicine Guidance Document no. 118; Mass Spectrometry for Confirmation of the Identity of Animal Drug Residues, 2003; Scholar
  14. 13.
    Commission Decision Implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. Official J. Eur. Commun. 2002, 221, 8–36.Google Scholar
  15. 14.
    Bethem, R.; Boison, J.; Gale, J.; Heller, D.; Lehotay, S.; Loo, J.; Musser, S.; Price, P.; Stein, S. Establishing the fitness for purpose of mass spectrometric methods. J. Am. Soc. Mass Spectrom. 2003, 14, 528–541.CrossRefGoogle Scholar
  16. 15.
    NIST/EPA/NIH Mass Spectral Library. NIST Standard Reference Database 1A, 2002, NIST, Gaithersburg, MD.Google Scholar
  17. 16.
    Derived from code available through, contact author for details ( Scholar
  18. 17.
    Stein, S. E. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spectrom. 1999, 10, 770–781.CrossRefGoogle Scholar
  19. 18.
    Pesyna, G. M.; Venkataraghavan, R.; Dayringer, H. E.; McLafferty, F. W. Probability based matching system using a large collection of reference mass spectra. Anal. Chem. 1976, 48, 1362–1368.CrossRefGoogle Scholar
  20. 19.
    Wan, K. X.; Vidavsky, I.; Gross, M. L. Comparing similar spectra: From similarity index to spectral contrast angle. J. Am. Soc. Mass Spectrom. 2002, 13, 85–88.CrossRefGoogle Scholar

Copyright information

© American Society for Mass Spectrometry 2006

Authors and Affiliations

  1. 1.NIST Mass Spectrometry Data Center, A111/221GaithersburgUSA
  2. 2.FDA Center for Veterinary MedicineLaurelUSA

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