One more question. I am using COMET prior to the peptide prophet steps. 
COMET is already generating decoy database (concatenated search), do I need 
to turn the decoy search off in COMET?

On Tuesday, May 14, 2024 at 2:38:00 PM UTC+5:30 Debojyoti Pal wrote:

> Thank you Dr David! That is really great help. 
>
> I have a couple  of follow-up queries:
>
> 1) If I use iProphet on these results, does that now use Decoy based FDR 
> estimates or the PeptideProphet statisitcal model only estimates.
>
> 2) If I combine multiple PeptideProphet outputs (from fractions of same 
> digest) in iProphet , how does that affect individual PSMs? For example, if 
> a PSM if found in multiple fractions, does it get converted to single PSM 
> in the iProphet output (I just want to make the output compatible to 
> MSStatsTMT - see here https://groups.google.com/g/msstats/c/aINhWMKt2Co) 
> While MSStatsTMT has converters for other SW like Maxquant and PD, I kind 
> of like TPP, so trying to establish a proper workflow for my fractionated 
> TMT data.
>
> Thanks again,
> Debojyoti
>
> On Sunday, May 12, 2024 at 10:54:18 PM UTC+5:30 David Shteynberg wrote:
>
>> Dear Debojyoti,
>>
>> Welcome to the world of TPP!
>>
>> If you have a database of targets you can use the following tool in TPP 
>> to generate random (repeat preserving deBruijn) decoys for your targets:
>>
>> [image: image.png]
>>
>> With the default options this tool will create two independent sets 
>> decoys for each of your targets, prefixed by DECOY0 and DECOY1.
>>
>> After you search the data you can analyze it with PeptideProphet in many 
>> different ways.  I would suggest you try with the following options to 
>> start:
>>
>> [image: image.png]
>>
>> This will enable PeptideProphet to use DECOY0 hits as model-decoys and 
>> DECOY1 hits as validation-decoys.
>>
>> With these setting the table on the models page will contain model-based 
>> error estimations based on the model trained with DECOY0 ("known" decoys).
>>
>> As part of the run with these settings DECOY1 will be used to validate 
>> the PeptideProphet model using the "unknown" decoys.  This will be 
>> displayed on the models page "Models Charts" tab near the bottom, for 
>> example:
>> [image: image.png]
>>
>> The chart on the right shows both the "DECOY" (DECOY1 "unknown") ROC 
>> curve and the "PREDICTED" (DECOY0 "known" model-based) ROC curve.  The 
>> error estimates comparing the model-based error to the unknown/validation 
>> decoy-based error are on the chart on the left.  If you want evaluate a 
>> model using a different decoys settings you can run the ProphetModels.pl 
>> decoy validation tool on the following page:
>> [image: image.png]
>>
>> On this page set the decoy proteins to the PeptideProphet "model unknown" 
>> and the excluded decoys to the PeptideProphet "model known' ones (if any) 
>> as follows:
>> [image: image.png]
>>
>> Hopefully this helps you process your dataset.  Let us know if you have 
>> additional questions.
>>
>> Cheers!
>> -David
>>
>>
>>
>> On Sun, May 12, 2024 at 2:38 AM Debojyoti Pal <[email protected]> 
>> wrote:
>>
>>> Hello everyone
>>>
>>> Proteomics newbie here. I am trying to use TPP and peptide prophet but 
>>> really unable to understand the options and outputs. Seeking help of the 
>>> experienced members.[image: peptideprophet.PNG]
>>>
>>> What are the options that I need to activate to estimate FDR via the 
>>> target-decoy mode? I am currently generation decoy through comet and 
>>> actuvation "use decoy hits to pin down" option and "known protein names 
>>> begin with" option and "use non parametric model option". What do the 
>>> option "report decoy hits with computed probability do? And the other 
>>> options too? 
>>>
>>> [image: results.PNG]
>>>
>>> How is this decoy based FDR calculated?? I am not asking the principle 
>>> behind it but I can't see a table for the same? And what is the FDR after 
>>> discard?
>>>
>>> [image: table.PNG]
>>>
>>> The data in this table is not for decoy based FDR, right? This is the 
>>> peptide prophet stattistical model based FDR, correct?
>>>
>>> I would be highly obliged if anyone could help me out. 
>>>
>>> Thanks
>>> Debojyoti 
>>> PhD Student
>>>
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>>>
>>

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