Methods for time-alignment of liquid chromatography-mass spectrometry data
View Patent ↗Nonlinear retention time variations in chromatography-mass spectrometry data sets are adjusted by time-alignment methods, enabling automated comparison of spectra for differential phenotyping and other applications.
1. A program storage device accessible by a processor, tangibly embodying a program of instructions executable by said processor to perform method steps for a method for time-aligning chromatography-mass spectrometry data sets, each comprising a plurality of mass chromatograms, said method steps comprising:
a) receiving data generated by a mass spectrometer;
b) computing a distance function between said data sets in dependence on at least two mass chromatograms from each data set; and
c) aligning said data sets by minimizing said distance function to obtain aligned data sets.
2. A program storage device accessible by a processor, tangibly embodying a program of instructions executable by said processor to perform method steps for a method for time-aligning two-dimensional chromatography-mass spectrometry data sets, said method steps comprising:
a) receiving data generated by a mass spectrometer;
b) selecting peaks in said data sets;
c) identifying potentially corresponding peaks from said selected peaks; and
d) performing a locally-weighted regression smoothing on said potentially corresponding peaks to obtain aligned data sets.
3. The program storage device of claim 2 , wherein the step of selecting of peaks is performed automatically.
4. The program storage device of claim 2 , wherein one of said data sets is a reference data set and one of said data sets is a test data set, and wherein said test data set is aligned to said reference data set.
5. The program storage device of claim 2 , wherein said data sets are liquid chromatography-mass spectrometry data sets.
6. The program storage device of claim 2 , wherein the step of performing said locally-weighted regression smoothing is a robust locally-weighted regression smoothing.
7. The program storage device of claim 6 , wherein said robust locally-weighted regression smoothing comprises robust LOESS.
8. The program storage device of claim 2 , wherein the said step of performing said locally-weighted regression smoothing is performed in dependence on a span.