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Laboratory
for ChemoMetrics,
Vienna (Austria) MS - Chemometrics - COSIMA |
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Summary of Results: Chemometrics with PDMS Data Mass Spectra Transformation |
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An appropriate mathematical transformation of the original peak list
data into a set of suitable features is essential for a successful application
of multivariate data analysis.
A spectral feature xj is a number
that can be automatically computed from a spectrum.
Often nonlinear transformations are applied that sometimes consider spectroscopic
knowledge. Aim of data transformation is to obtain a set of variables that are better
suited for a structure related spectra interpretation than the original
peak list data.
Some of the spectral features used for the PDMS spectra have already
been described for EI mass spectra, others were
developed for the particular ion fragmentation reactions occurring in
SIMS and PDMS.
All features are calculated from mass spectra which were normalized to
the base peak intensity. All features are scaled to the range 0 to 100. The
total number of features used in this work is 708.
Thus each mass spectrum is represented by 708 variables.
Spectral features used for multivariate data analysis of PDMS
spectra.
|
feature
group |
feature description |
no of features |
|
1 |
intensities (% base peak) at single masses (m/z 25-38,
40-150) |
125 |
|
2 |
intensities at single masses normalized to local ion
current (window of 7 masses, m/z 25-38, 40-150) |
125 |
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3 |
averaged intensities of mass ranges m/z 25-38, 40-70,
71-100, 101-150 |
4 |
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4 |
logarithmic intensity ratios, m/z 25-38 and 40-150 with
mass differences of 1 and 2 |
250 |
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5 |
modulo-14 summation for mass ranges 25-120, 25-250, and
121-250 |
42 |
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6 |
autocorrelation for mass differences of 1, 2, and 14-60
in mass ranges 25-120, 25-250, and 100-250 |
147 |
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7 |
spectra type features describing the distribution of
peaks |
3 |
|
8 |
peak series features that characterize the joint presence
of peaks at given masses |
12 |
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Last update 2000-12-03 |
