|MS1 Quantification of Precursor Ions||brown459||2019-05-15|
The problem: We have generated a database of glycopeptide identifications using a DDA analysis. Each sample/acquisition (i.e. run 1 through run 26) is a high pH reverse phase chromatography fraction. Therefore, not every acquisition contains each of the glycopeptides identified in the database. In fact each glycopeptide should only be observed in a few runs. We want to quantify the abundance of individual glycopeptides in the identified fraction (run) and the surrounding runs.
Is there a way to use Skyline to very simply, export XIC's for a series (we define) of amino acids modified with variable glycoforms (~300). We have the m/z, charge, RT, fraction, elemental composition. We also have a .blib that is composed of EThcD spectra.
I have approached this problem from both the proteomics and the molecule interfaces and have encountered similar erroneous peak matchings. Because we do not identify every species in each fraction, we are finding that in fractions where a glycopeptide is not observed, skyline ends up quantifying an incorrect precursor MS1 that is near it in RT.
Molecules doesn't seem to restrict IDs based on the explicit retention time window. Proteomics may be the only way to go, using MS1 quant and really reducing the RT window? This however, seems to take a long time as there are many possible combinations of modifications.
Are there any other work arounds that I am not thinking of?