Journal
ANALYTICAL CHEMISTRY
Volume 84, Issue 15, Pages 6477-6487Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ac301350n
Keywords
-
Categories
Funding
- National Institute of General Medical Sciences (NIGMS) within the National Institute of Health (NIH) [1RO1GM087735]
- Department of Energy (DOE) [DE-EM0000197]
- Office of the Executive Vice President for Research
Ask authors/readers for more resources
Compound identification is a key component of data analysis in the applications of gas chromatography-mass spectrometry (GC-MS). Currently, the most widely used compound identification is mass spectrum matching, in which the dot product and its composite version are employed as spectral similarity measures. Several forms of transformations for fragment ion intensities have also been proposed to increase the accuracy of compound identification. In this study, we introduced partial and semipartial correlations as mass spectral similarity measures and applied them to identify compounds along with different transformations of peak intensity. The mixture versions of the proposed method were also developed to further improve the accuracy of compound identification. To demonstrate the performance of the proposed spectral similarity measures, the National Institute of Standards and Technology (NIST) mass spectral library and replicate spectral library were used as the reference library and the query spectra, respectively. Identification results showed that the mixture partial and semipartial correlations always outperform both the dot product and its composite measure. The mixture similarity with semipartial correlation has the highest accuracy of 84.6% in compound identification with a transformation of (0.53,1.3) for fragment ion intensity and m/z value, respectively.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available