I am not convinced that turning this model off creates a huge difference.
You can run the analysis both ways and consider the best results.

On Tue, Mar 1, 2016 at 1:38 PM, John Damask <jbdam...@gmail.com> wrote:

> Hello David,
> Thanks very much for your response.
>
> Your slides from a TPP course (a couple of years old, now) state that
> iProphet's NSP model "Should be turned off when ProteinProphet NSP model
> is used". Is this still the recommendation? In the post I originally
> linked to, wrt NSP in iProphet and ProteinProphet, you state that you "have
> not found the two to interfere" which reads to me like it can be used in
> both.
>
> John
>
>
> On Friday, February 19, 2016 at 2:24:06 PM UTC-5, David Shteynberg wrote:
>>
>> Hello John,
>>
>> Thank you for your question.
>>
>> NSP in iProphet looks at all proteins that a given peptide matches, it
>> then sums the probabilities of all the other peptides that match the same
>> protein.  For a given peptide it then takes as the NSP the maximum such sum
>> over all the proteins matched. It is a bit different from NSP in
>> ProteinProphet since in ProteinProphet a given peptide has a different NSP
>> in each protein it appears.
>>
>> -David
>>
>> On Fri, Feb 19, 2016 at 11:04 AM, John Damask <jbda...@gmail.com> wrote:
>>
>>> Hi,
>>>
>>> I'm interested in learning more about how iProphet's NSP model works.
>>> The original paper doesn't discuss it as a first class iProphet model and
>>> Fig1 only shows it in ProteinProphet.
>>>
>>> In this post
>>> <https://groups.google.com/forum/#!searchin/spctools-discuss/iprophet$20nsp/spctools-discuss/mLAMdJUP8AQ/wGQfI0061scJ>
>>> David states "I have found that applying the NSP model at the iProphet step
>>> greatly improves performance on peptide level". But what is it doing,
>>> exactly?
>>>
>>> Thanks for providing such great software to the community!
>>> John
>>>
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