Glycan identification in "combined_modified_peptide.tsv" file

[mwfoster]

Hi,

We are performing glycopeptide identification and quantification across many samples. The data in the "assigned modifications" column of the "combined_modified_peptide.tsv" file gives only the mass of the glycan, not the ID. I gather from a previous post that the "psm.tsv" contains the information to connect the "assigned modification" to the "observed modification" that would be found in the glycan database. However, since the psm.tsv is specific to a sample, this could require performing this lookup on a large number of psm.tsv files. Is there an easier way to do this, or could you modify the "combined_modified_peptide.tsv" to include the best match to the glycan database?

Thanks,

Matt

[dpolasky]

Hi Matt,

There is not an easier way to do this at the moment, unfortunately. I think we could add the Observed Modifications column to the combined_modified_peptide.tsv @fcyu? Or we may need to discuss internally the best way to propagate the glycan information.

Best, Dan

[fcyu]

Yes, we can let IonQuant take that information and propagate to the combined table.

Best,

Fengchao

[mwfoster]

Thanks. That would be very helpful. Regards, Matt

[ShinjaChakraborty]

Hi, could you please provide me the detailed protocol to run Fragpipe for N glycopeptides identification?

[fcyu]

Hi @ShinjaChakraborty , you could start with one of the built-in glyco-N workflows. Here is a tutorial if you need it: https://fragpipe.nesvilab.org/docs/tutorial_glyco.html

Best,

Fengchao

[ShinjaChakraborty]

I am getting error in Proteinprophet log_2024-08-09_23-27-33.txt

[fcyu]

Same reason, there are no IDs

WARNING: Mixture model quality test failed for charge (2+).
WARNING: Mixture model quality test failed for charge (3+).
WARNING: Mixture model quality test failed for charge (4+).
WARNING: Mixture model quality test failed for charge (5+).
WARNING: Mixture model quality test failed for charge (6+).
WARNING: Mixture model quality test failed for charge (7+).

...read in 0 1+, 0 2+, 0 3+, 0 4+, 0 5+, 0 6+, 0 7+ spectra with min prob 0.05

Best,

Fengchao