Peptide to protein TMT quan value transfer

[RuzMn]

I'm using philosopher.yml for TMT quantification. I noticed that even though I don't apply any normalisation or correction the TMT abundances on peptide level differ from the abundances on protein level. This can be seen for the proteins quantified with a single peptide, as in the example below. How can this be explained? Is there any automatic correction applied during peptide to protein TMT quan value transfer?

channel_126	channel_127N	channel_127C	channel_128N	channel_128C	channel_129N	channel_129C	channel_130N	channel_130C

peptide 250143.8535 173876.6582 247954.2891 1150771.109 1237605.828 1223634.578 353469.2031 272314.7305 400221.9277 protein 130404.7655 59140.2925 148524.6393 1150771.109 888926.1563 897012.2277 197173.7691 90271.1594 207421.6747

[fcyu]

I am not sure if I follow your question, but the peptide abundance is supposed to be different from the protein abundance due to the nature of two subjects and the algorithm. Can you elaborate your question a little bit more?

Thanks,

Fengchao

[RuzMn]

Hi Fengchao,

Yes, sure.

Protein abundance is calculated based on the peptide abundance. Here for the protein which is quantified with a single peptide, this means that if no correction is applied the protein abundance should be equal to the abundance of this peptide, but the abundances are not matching. There is only one channel that is matching (128N with abundance of 1150771.109) in both protein and peptide level, the other channels are somehow corrected or normalised, but as I specifically select the option to report the quan results without normalisation this is weird. It means that the script is normalising my data, even though I select to not too.

Best,

Ruzanna

From: Fengchao @.> Sent: 07 June 2022 14:04 To: Nesvilab/FragPipe @.> Cc: RuzMn @.>; Author @.> Subject: Re: [Nesvilab/FragPipe] Peptide to protein TMT quan value transfer (Issue #704)

I am not sure if I follow your question, but the peptide abundance is supposed to be different from the protein abundance due to the nature of two subjects and the algorithm. Can you elaborate your question a little bit more?

Thanks,

Fengchao

— Reply to this email directly, view it on GitHub https://github.com/Nesvilab/FragPipe/issues/704#issuecomment-1148574193 , or unsubscribe https://github.com/notifications/unsubscribe-auth/AZQTGSTFDROIZMX66BGSCVTVN43CFANCNFSM5YCDTY5Q . You are receiving this because you authored the thread. https://github.com/notifications/beacon/AZQTGSW4OWB557METLASVA3VN43CFA5CNFSM5YCDTY52YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOIR25T4I.gif Message ID: @.*** @.***> >

[anesvi]

Felipe, it would be good if you can check this, as quant in peptide.tsv and protein.tsv files is computed by philosopher

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From: RuzMn @.> Sent: Tuesday, June 7, 2022 7:14:18 AM To: Nesvilab/FragPipe @.> Cc: Subscribed @.***> Subject: Re: [Nesvilab/FragPipe] Peptide to protein TMT quan value transfer (Issue #704)

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Hi Fengchao,

Yes, sure.

Protein abundance is calculated based on the peptide abundance. Here for the protein which is quantified with a single peptide, this means that if no correction is applied the protein abundance should be equal to the abundance of this peptide, but the abundances are not matching. There is only one channel that is matching (128N with abundance of 1150771.109) in both protein and peptide level, the other channels are somehow corrected or normalised, but as I specifically select the option to report the quan results without normalisation this is weird. It means that the script is normalising my data, even though I select to not too.

Best,

Ruzanna

From: Fengchao @.> Sent: 07 June 2022 14:04 To: Nesvilab/FragPipe @.> Cc: RuzMn @.>; Author @.> Subject: Re: [Nesvilab/FragPipe] Peptide to protein TMT quan value transfer (Issue #704)

I am not sure if I follow your question, but the peptide abundance is supposed to be different from the protein abundance due to the nature of two subjects and the algorithm. Can you elaborate your question a little bit more?

Thanks,

Fengchao

— Reply to this email directly, view it on GitHub https://github.com/Nesvilab/FragPipe/issues/704#issuecomment-1148574193 , or unsubscribe https://github.com/notifications/unsubscribe-auth/AZQTGSTFDROIZMX66BGSCVTVN43CFANCNFSM5YCDTY5Q . You are receiving this because you authored the thread. https://github.com/notifications/beacon/AZQTGSW4OWB557METLASVA3VN43CFA5CNFSM5YCDTY52YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOIR25T4I.gif Message ID: @.*** @.***> >

— Reply to this email directly, view it on GitHubhttps://github.com/Nesvilab/FragPipe/issues/704#issuecomment-1148584733, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIIMM67RJV4HW5MIHD26SL3VN44JVANCNFSM5YCDTY5Q. You are receiving this because you are subscribed to this thread.Message ID: @.***>

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[prvst]

@RuzMn Are you comparing the values from The PSM or peptide table to the protein table, or against the TMT-Integrator tables?

[RuzMn]

@RuzMn Are you comparing the values from The PSM or peptide table to the protein table, or against the TMT-Integrator tables?

Peptide table

[prvst]

When you search the PSM table for the protein ID or accession number, how many hits do you get? Look for both the main protein identification and the alternative proteins.