Precursor.Mz Definition and Request

[jens-decker-bruker]

Hi,
I would like to use the search results from DIANN 2.0.1 for m/z calibration related purposes. Checking a few hits I´m not sure,
what is reported in the report.parquet file. Checking a random hit, AAAEVAGQFVIK with z=2 I got 602.340210 Da from DIANN, 602.340238 Da from an inhouse tool and manually checking things with isotope masses from https://physics.nist.gov/cgi-bin/Compositions/stand_alone.pl?ele=&all=all&ascii=html&isotype=some (not changed since 2015 according to their web page) I get (5512.0+921.00782503223+1414.00307400443+1615.99491461957-2*5.485799090441e-4)/2 = 602.3402378902409. So there is deviation of 28 uDa between the reported values and the true theoretical values.

Correct assumption that this is due to some 32 bit float rounding (other deviations where +22 uDa, -26 uDa, slightly below the deviation to be expected from float? Was reading in things with Python/Pandas.

What I would like to suggest and get in addition would be the experimental m/z (with and especially without internal recalibration done by DIANN).
Best Regards,
Jens

[vdemichev]

Hi Jens,

The .parquet report contains the theoretical precursor m/z and an empirical non-calibrated mass deviation, i.e. if you sum the two values, you can get the observed empirical mass.

The theroretical masses as calculated by DIA-NN indeed are rounded to 32-bit. The calculation may also be affected by the precision of constants for proton & amino acid masses. In fact, the difference between 602.340238 and 602.340210 you quote is just 47ppb (i.e. < 0.05 ppm), which would be completely negligible even for FT-ICR.

Best,
Vadim

[jens-decker-bruker]

Hi Vadim,

thanks for you instant reply! Whats the name of that m/z deviation, some option to be set to get it exported? Can't find it in the list of columns Pandas shows me with print(df.head().to_string()).
Thanks,
Jens

Run.Index Run Channel Precursor.Id Modified.Sequence Stripped.Sequence Precursor.Charge Precursor.Lib.Index Decoy Proteotypic Precursor.Mz Protein.Ids Protein.Group Protein.Names Genes RT iRT Predicted.RT Predicted.iRT IM iIM Predicted.IM Predicted.iIM Precursor.Quantity Precursor.Normalised Ms1.Area Ms1.Normalised Ms1.Apex.Area Ms1.Apex.Mz.Delta Normalisation.Factor Quantity.Quality Empirical.Quality Normalisation.Noise Ms1.Profile.Corr Evidence Mass.Evidence Channel.Evidence Ms1.Total.Signal.Before Ms1.Total.Signal.After RT.Start RT.Stop FWHM PG.TopN PG.MaxLFQ Genes.TopN Genes.MaxLFQ Genes.MaxLFQ.Unique PG.MaxLFQ.Quality Genes.MaxLFQ.Quality Genes.MaxLFQ.Unique.Quality Q.Value PEP Global.Q.Value Lib.Q.Value Peptidoform.Q.Value Global.Peptidoform.Q.Value Lib.Peptidoform.Q.Value PTM.Site.Confidence Site.Occupancy.Probabilities Protein.Sites Lib.PTM.Site.Confidence Translated.Q.Value Channel.Q.Value PG.Q.Value PG.PEP GG.Q.Value Protein.Q.Value Global.PG.Q.Value Lib.PG.Q.Value

[vdemichev]

Ms1.Apex.Mz.Delta

[jens-decker-bruker]

Thanks a lot! Delta = ExpMz-TheorecticalMz?

[vdemichev]

Yes