p value for this example should be just under .95, p value of 0.9 that you
were using will give you 2.1% FDR. I almost always run MAYU on my results
and that tells the p Value corresponding to 1% FDR at protein level.


On Wed, Mar 20, 2013 at 3:40 PM, Sandeep <[email protected]> wrote:

> Thanks for you answer. I want to make sure my calculation is correct. The
> details of protein prophet result is -
>
> *Minimum probability**Sensitivity**Error rate*0.00 1.00000.89600.101.0000
> 0.23900.201.00000.23900.300.96700.17800.400.9410 0.14600.500.90700.1170
> 0.600.86300.08900.700.80800.06400.800.73900.0420 0.900.62900.02100.95
> 0.52100.00900.960.50100.00700.970.47400.00600.98 0.41300.00300.990.3690
> 0.00101.000.08600.0000
>
>
> Based on this result, what is
> probability cutoff that gives me 1% FDR?
>
> Thanks
>
> Sandeep
>
>
>
>
>
> On Friday, March 15, 2013 11:01:24 AM UTC-5, kshitiz wrote:
>
>> Sorry I probably was not clear enough. Number of unique peptides for a
>> protein are actually number of PSMs, so hypothetically if a protein was
>> identified based on one peptide that was fragmented 10 times and 8 out of
>> those 10 ms/ms spectra result in peptide spectrum match , then number of
>> unique peptides will read 8 however you have identified only one peptide.
>>
>> I hope someone on the forum can correct me if I am wrong.
>>
>> Additionally, you said that you filter at p > 0.9, this is not very
>> informative and not the best way of filtering. Instead you should filter at
>> a p value that controls for less than 1% FDR.
>>
>> cheers
>>
>>
>> On Fri, Mar 15, 2013 at 3:05 PM, Sandeep <[email protected]> wrote:
>>
>>> Hello,
>>>
>>>   Sorry, I think I did not understand your answer. My concern was- why I
>>> have more number of unique peptides as compared to TOTAL number of peptides
>>> in my data after protein prophet grouping and filtering my data to contain
>>> only groups with probability more than 0.9.
>>>
>>> Thanks
>>>
>>> Sandeep
>>>
>>>
>>>
>>>
>>> On Friday, March 15, 2013 3:41:11 AM UTC-5, kshitiz wrote:
>>>>
>>>> Hi,
>>>> I think the number given under number of unique peptides is actually
>>>> number of unique PSMs used for the identity of that protein. If you want
>>>> actual number of unique peptides then you will have to pull the data into
>>>> an SQL based server and then query it to to count distinct peptides for
>>>> each protein.
>>>>
>>>> cheers.
>>>>
>>>>
>>>> On Thu, Mar 14, 2013 at 10:00 PM, Sandeep <[email protected]> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I have recently started using peptide/proteinprophet. I noticed that
>>>>> in my data, there are several protein groups for which the number of 
>>>>> unique
>>>>> peptidees is more than the number of total peptides (mostly the total
>>>>> number of peptides is 0). Is this data reliable? How to explain this.
>>>>> Thanks in advance for any answers.
>>>>>
>>>>> Sandeep
>>>>>
>>>>>
>>>>>
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>>>>
>>>>
>>>> --
>>>> Kshitiz Tyagi
>>>>
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