Thanks so much David for your response. It makes sense.

All the best,
Soroush

On Wednesday, January 20, 2021 at 11:54:12 PM UTC-5 David Shteynberg wrote:

> This option changes the way mixture models in the TPP (PeptideProphet) are 
> generated.  The probabilities are estimated based on the mixture models 
> learned by PeptideProphet.  When the mixture models change so will the 
> probabilities.
>
> On Wed, Jan 20, 2021 at 8:44 PM Soroush F <[email protected]> wrote:
>
>> Dear David,
>>
>> Thanks so much for your time answering my questions.
>>
>> I gather from your answer that this option is for TPP. If that is the 
>> case, why does the PeptideProphet probabilities changes when selecting the 
>> option? Am I missing something?
>>
>> Many thanks.
>> Soroush
>>
>> On Tuesday, January 19, 2021 at 2:59:56 PM UTC-5 David Shteynberg wrote:
>>
>>> Dear Soroush,
>>>
>>> This option makes use of the TPP's semi-supervised learning mode, which 
>>> can be used in conjunction with semi-parametric mode, at the user's 
>>> discretion.  Until now, some search engines supported by TPP analysis could 
>>> only be modeled by PeptideProphet using semi-parametric and semi-supervised 
>>> that required decoys to be used in the search.  Going forward with the new 
>>> version of the TPP (pre-release version 6.0.0) this is not going to be 
>>> the case as we will be providing both types of models for more search 
>>> engine results.  I hope this answers your question.
>>>
>>> Cheers,
>>> -David
>>>
>>> On Mon, Jan 18, 2021 at 4:02 PM Soroush F <[email protected]> wrote:
>>>
>>>> Dear all,
>>>>
>>>> I was wondering when one should use "Use decoy hits to pin down the 
>>>> negative distribution" in the Peptide Prophet (run through Petunia)?
>>>>
>>>> If I want to use Target-Decoy approach to estimate FDR in my analysis, 
>>>> should I use this box, or it has nothing to do with it?
>>>>
>>>> Thanks,
>>>> Soroush
>>>>
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