DDA to DIA (MSE) Peak Peaking Errors | Juan C. Rojas E. | 2021-05-06 05:01 | |||||||||||||||||||||||||||||||||||||||||
Hi All, I'm following this general workflow from data generated from a Synapt G2-Si using multiple DDA and MSE methods:
What I have observed in multiple datasets is that in many instances Sykline is defining the peak boundaries that fit a good dotp with respect to the spectral library but ignores the fit of the peak boundaries to the precursor ions. This happens when there are closely eluting peptides with similar sequence missing or having extra one or two amino acids (using semi-specific digest results) where the peptide happens to have higher total area for the fragments AUC but there is no detectable signal for the peptide in the precursor scan (low energy scan; Slide 1). The result is in inflated coefficients of variation just because of bad, automatic peak picking (Slide 2, Fig. 1) that can be resolved (Slide 2, Fig. 2) if I check for all peptides in the document. Unfortunately, I don't work with SWATH-like data, but I would assume this is not an issue that that approach would have (or at least less frequently) since the fragments would not be binned with the m/z range of the "interferring" peptide. Is this an issue specific to MSE or is there something I am overlooking in the data import? If indeed this is an all-ion-fragmentation issue, is there any solution that could be implemented? I have prepared two sample set examples that can be found in our U of Leipzig Panorama space under seMSE called: Raw import: Curated results: I can think of some "tricks" to avoid these issues using the IMS information collected (for the files containing IMS data), but I would like to explore the only m/z dimension solutions that can be applied on the initial data import without having to train an mProphet model (this is pending to test on this data to see if it would help). As always, thanks for the time and help. |
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