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 computer-implemented method for time-aligning at least two chromatography-mass spectrometry data sets, each comprising a plurality of mass chromatograms, said method comprising:
a) computing a distance function between said data sets in dependence on at least two mass chromatograms from each data set; and
b) aligning said data sets by minimizing said distance function to obtain aligned data sets.
2. The method of claim 1 , 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.
3. The method of claim 1 , wherein said data sets are liquid chromatography-mass spectrometry data sets.
4. The method of claim 1 , wherein said distance function is computed in dependence on between about 200 and about 400 mass chromatograms from each data set.
5. The method of claim 1 , further comprising selecting said at least two mass chromatograms according to a selection criterion.
6. The method of claim 1 , wherein said distance function is computed in dependence on a chromatogram-dependent weighting factor.
7. The method of claim 6 , wherein said chromatogram-dependent weighting factor is a function of at least one of a peak number, an intensity threshold, and a signal-to-noise ratio.
8. A method for comparing at least two samples, comprising:
a) performing chromatography-mass spectrometry on each sample to obtain at least two data sets, each comprising a plurality of mass chromatograms;
b) computing a distance function between two selected data sets in dependence on at least two mass chromatograms from each selected data set;
c) aligning said selected data sets by minimizing said distance function to obtain aligned selected data sets; and
d) comparing said aligned selected data sets.
9. The method of claim 8 , wherein one of said selected data sets is a reference data set and another of said selected data sets is a test data set, and wherein said test data set is aligned to said reference data set.
10. The method of claim 8 , wherein said chromatography-mass spectrometry is liquid chromatography-mass spectrometry.
11. The method of claim 8 , further comprising aligning two additional data sets, wherein at least one of said additional data sets differs from said selected data sets.
12. The method of claim 8 , further comprising selecting said at least two mass chromatograms according to a selection criterion.
13. The method of claim 12 , wherein said selection criterion is a user-provided selection criterion.
14. The method of claim 12 , wherein said selection criterion comprises an intensity threshold.
15. The method of claim 12 , wherein said selection criterion comprises a number of chromatograms.
16. The method of claim 12 , wherein said selection criterion comprises an orthogonality metric.
17. The method of claim 12 , wherein said selection criterion comprises a retention time range.
18. The method of claim 8 , wherein said distance function is computed in dependence on between about 200 and about 400 mass chromatograms.
19. The method of claim 8 , wherein said distance function is computed in dependence on between about 200 and about 300 mass chromatograms.
20. The method of claim 8 , wherein said distance function is computed in dependence on about 200 mass chromatograms.
21. The method of claim 8 , wherein said distance function is computed in dependence on a weighting factor.
22. The method of claim 21 , wherein said weighting factor is a chromatogram-dependent weighting factor.
23. The method of claim 22 , wherein said chromatogram-dependent weighting factor is a function of at least one of a peak number, an intensity threshold, and a signal-to-noise ratio.
24. The method of claim 8 , further comprising identifying features that differentiate said aligned selected data sets.
25. A method for identifying a biomarker differentiating two cohorts, comprising:
a) comparing at least two samples according to the method of claim 10 , at least one each of said samples representing a different one of said two cohorts; and
b) identifying a biomarker in dependence on said comparison.
26. A diagnostic method comprising detecting a biomarker identified by the method of claim 25 .
27. A computer-implemented method for time-aligning at least two two-dimensional chromatography-mass spectrometry data sets, comprising:
a) selecting peaks in said data sets;
b) identifying potentially corresponding peaks from said selected peaks; and
c) performing a locally-weighted regression smoothing on said potentially corresponding peaks to obtain aligned data sets.
28. The method of claim 27 , 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.
29. The method of claim 27 , wherein said data sets are liquid chromatography-mass spectrometry data sets.
30. The method of claim 27 , wherein said locally-weighted regression smoothing is a robust locally-weighted regression smoothing.
31. The method of claim 30 , wherein said robust locally-weighted regression smoothing comprises robust LOESS.
32. The method of claim 27 , wherein said peaks are selected automatically.
33. The method of claim 27 , wherein said locally-weighted regression smoothing is performed in dependence on a span.
34. A method for comparing at least two samples, comprising:
a) performing chromatography-mass spectrometry on each sample to obtain at least two two-dimensional data sets;
b) selecting peaks in two selected data sets;
c) identifying potentially corresponding peaks from said selected peaks;
d) performing a locally-weighted regression smoothing on said potentially corresponding peaks to obtain aligned selected data sets; and
e) comparing said aligned selected data sets.
35. The method of claim 34 , wherein one of said selected data sets is a reference data set and another of said selected data sets is a test data set, and wherein said test data set is aligned to said reference data set.
36. The method of claim 34 , wherein said chromatography-mass spectrometry is liquid chromatography-mass spectrometry.
37. The method of claim 34 , further comprising aligning two additional data sets, wherein at least one of said additional data sets differs from said selected data sets.
38. The method of claim 34 , further comprising identifying features that differentiate said aligned selected data sets.
39. A method for identifying a biomarker differentiating two cohorts, comprising:
a) comparing at least two samples according to the method of claim 34 , at least one each of said samples representing a different one of said two cohorts; and
b) identifying a biomarker in dependence on said comparison.