Thanks a lot Kshitiz for your prompt replies and helping me. I have a one 
more question, when you run protein prophet to get the protein groups with 
1% FDR cutoff, do you ALSO use peptides with 1% FDR cutoff for the protein 
assignments? 

Thanks

Sandeep



On Wednesday, March 20, 2013 12:14:34 PM UTC-5, kshitiz wrote:
>
> 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]<javascript:>
> > 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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>>>
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>>>
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>
> -- 
> Kshitiz Tyagi
>
>  

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