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 <sor...@gmail.com> 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 <sor...@gmail.com> 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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