Hi Jesse,

Thanks for helping. Sorry for late reply, as I was out of station with no
access to mail.
I will step forward with comet search + Peptideprophet.

Regards
Ankit




On Fri, 15 Feb 2019 at 20:50, Jesse Meyer <[email protected]> wrote:

> Hi Ankit,
>
> Actually I see now it does find peptides from the X!tandem search, it
> first tells you:
>
> Found 676 Decoys, and 834 Non-Decoys
>
> That is a low number of peptide hits for what I gather from your filenames
> is a liver sample. That might be why your models are failing because they
> need some minimum per charge to pass. I recommend checking if the X!tandem
> search output before PeptideProphet finds a similar number of peptides as
> your comet search.
>
> In my experience, you should get similar results with msconvert vs sciex
> converter. You can rule this out by converting with the other one and
> comparing. You will get a slight improvement  using msconvert with the
> qtofpeakpicker flag compared to sciex or normal msconvert. The conversion
> will only influence PeptideProphet indirectly by changing your number of
> hits because although it tries to look for your raw data I don't think it
> actually needs to unless you want the TPP GUI to associate the two for
> viewing spectra in your browser.
>
> In the end, if your comet search + PeptideProphet works you might just go
> with that. You do get more by combining searches but for most projects I'm
> left with more changes than I can interpret anyway.
>
> Good luck and best regards,
> Jesse
>
>
> Jesse G. Meyer, Ph.D.
> Postdoctoral Fellow
> Coon Lab
> Department of Chemistry
> Department of Biomolecular Chemistry
> National Center for Quantitative Biology of Complex Systems
> University of Wisconsin - Madison
> [email protected]
>
>
> On Thu, Feb 14, 2019 at 2:00 PM Ankit Balhara <[email protected]>
> wrote:
>
>> Hi Jesse,
>>
>> Thanks for helping. I also tried the same data on comet also, it is
>> showing no errors. And I am using same fasta and mass tolerances for comet
>> search also, and its peptideprophet results are showing no errors.
>> As I have mentioned that I am using msconvert directly but not AB Sciex
>> converter for data conversion, could this be the reason of it. Also, I have
>> attached the tandem parameters file, could you please have a look into that
>> also.
>>
>> Thanks
>> Ankit
>>
>> On 15-Feb-2019 00:43, "Jesse Meyer" <[email protected]> wrote:
>>
>>> Hi Ankit,
>>>
>>> I've seen this before when my search doesn't produce any hits - usually
>>> the mixture model fails for only charge 1+, 6+, 7+ because I set the
>>> instrument to not fragment those charge states, but your model failed all
>>> of them.  Either there are no peptides in your samples, or your search
>>> settings were very wrong and that prevented you from finding any hits.
>>>
>>> I suggest checking your raw data's chromatogram for the presence of
>>> peptide peaks and also rich MS/MS spectra, and if you have those, then
>>> double check that you used the correct search settings (e.g. correct fasta,
>>> correct precursor/fragment tolerances, etc).
>>>
>>>
>>> Best,
>>>
>>> Jesse G. Meyer, Ph.D.
>>> Postdoctoral Fellow
>>> Coon Lab
>>> Department of Chemistry
>>> Department of Biomolecular Chemistry
>>> National Center for Quantitative Biology of Complex Systems
>>> University of Wisconsin - Madison
>>> [email protected]
>>>
>>>
>>> On Thu, Feb 14, 2019 at 12:27 PM Ankit Balhara <
>>> [email protected]> wrote:
>>>
>>>> Hi,
>>>>
>>>> I am using peptideprophet for the statistical validation of X!Tandem
>>>> results. I am using the options: Use accurate mass binning, using ppm, Use
>>>> Hydrophobicity / RT information, Use decoy hits to pin down the
>>>> negative distribution. Decoy protein names begin with'rev_', Use
>>>> Non-parametric model (can only be used with decoy option) and Report
>>>> decoy hits with a computed probability (based on the model learned). I have
>>>> acquired the data on AB Sciex system but I used msconvert for conversion of
>>>> .wiff files to mzXML format.
>>>> But I am getting the following error message:
>>>>
>>>> Found 676 Decoys, and 834 Non-Decoys
>>>> Iterations: .........10.........20.....Estimating Retention Time Model ... 
>>>> please wait ... WARNING: Not enough IDs in run index 
>>>> c:/TPP/data/liver_DDA_1 to generate RT Gradient Correction.WARNING: Not 
>>>> enough high probability IDs in run index c:/TPP/data/liver_DDA_1 to 
>>>> generate RT model. RT Model has been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_1, slope=nan, intercept=nan, 
>>>> r_sq=nanWARNING: Not enough IDs in run index c:/TPP/data/liver_DDA_2 to 
>>>> generate RT Gradient Correction.WARNING: Not enough high probability IDs 
>>>> in run index c:/TPP/data/liver_DDA_2 to generate RT model. RT Model has 
>>>> been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_2, slope=nan, intercept=nan, 
>>>> r_sq=nanWARNING: Not enough IDs in run index c:/TPP/data/liver_DDA_3 to 
>>>> generate RT Gradient Correction.WARNING: Not enough high probability IDs 
>>>> in run index c:/TPP/data/liver_DDA_3 to generate RT model. RT Model has 
>>>> been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_3, slope=nan, intercept=nan, 
>>>> r_sq=nanWARNING: Not enough high probability IDs in run index 
>>>> c:/TPP/data/liver_DDA_1 to generate RT model. RT Model has been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_1, slope=nan, intercept=nan, 
>>>> r_sq=nanWARNING: Not enough high probability IDs in run index 
>>>> c:/TPP/data/liver_DDA_2 to generate RT model. RT Model has been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_2, slope=nan, intercept=nan, 
>>>> r_sq=nanWARNING: Not enough high probability IDs in run index 
>>>> c:/TPP/data/liver_DDA_3 to generate RT model. RT Model has been disabled.
>>>> Run Index: c:/TPP/data/liver_DDA_3, slope=nan, intercept=nan, r_sq=nan
>>>>
>>>> WARNING: Mixture model quality test failed for charge (1+).WARNING: 
>>>> Mixture model quality test failed for charge (2+).WARNING: Mixture model 
>>>> quality test failed for charge (3+).WARNING: Mixture model quality test 
>>>> failed for charge (4+).WARNING: Mixture model quality test failed for 
>>>> charge (5+).WARNING: Mixture model quality test failed for charge 
>>>> (6+).WARNING: Mixture model quality test failed for charge (7+).
>>>> model complete after 26 iterations
>>>> command completed in 4 sec
>>>>
>>>>
>>>> Could anyone help me out to resolve this problem?
>>>>
>>>> I am also attaching the tandem parameter file also. Also the X!Tandem
>>>> results showed that the valid models for first data = 0, while 2 and 4
>>>> models for two other data.
>>>>
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