Calculating MS match values

As introduced in Section 8.4, a match value that shows how well the theoretical isotope distribution matches the measured intensities of the isotope peaks in the MS can be 

Calculation of isotope distributions based on precise masses gains importance in two cases. One is for large molecules, where the true mass differs considerably from the nominal mass. Several algorithms have been proposed for calculation of precise mass isotope distributions [253,254,255]. The second is for high resolution instruments such as Fourier transform ion cyclotron resonance (FT-ICR) and Orbitrap MS that are capable of resolving isotope fine structure, such that individual isotope peaks are seen for certain elements (e.g. S). The R package isopat implements the theory 

Where fine structure is present, this information can be used to define a more exact fuzzy formula for molecular formula candidate generation, significantly limiting the number of candidates. 

although we apply the unit mass assumption to the subsequent work presented here, an extension of the MS match value to account for exact masses and intensities of the individual isotope peeiks is possible and would provide further information during formula candidate selection. 

Comparing computed and measured isotope distributions is a vector compeuison between x = (xq,. xjt j) emd y = (yo, , yjt-i)- Methods for comparing two vectors include the scalar product (or dot product), the sum of absolute errors and the sum of squared errors. Normalizing these to give a match value between 0 and 1 yields three methods for calculating MS match values  

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In Subsection 8.8.2 we presented three match values for MS isotope peak comparison. Table 8.22 shows the number of formula candidates with at least one carbon atom as well as the absolute and relative ranking positions of the true formulas. Calculations are based on g and MS accuracy 5 = 10 ppm. Numbers in the row headers cross-reference with the compounds in Table 8.20. Using MS data alone, only two compounds have ARP = 1, of which one has only one possible candidate (i.e. a trivial result) and the other has only two possible candidates. Using the ARP, it is not possible to choose the best method for calculating MS match values. While NDP works best for most of the samples, NSSE yields the best result for maltopentaose, and NSAE is best for cyclosporin C. If we look at the RRP results, creatine is excluded (RRP is not defined for only one candidate), but calculation of the arithmetic mean is possible. Thus, it appears that NDP performs best on average for these ten samples, but the other methods deliver quite similar mean results, and considering the small number of samples, this conclusion is by no means a statistically reliable result. What is clear from these results, the MS match value alone is by no means sufficient to unambiguously determine the correct molecular formula in most cases without further information or restrictions. 

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