Apologies. 

Please find the database with decoy
https://drive.google.com/file/d/18ijaNWgmIompoJ0m99V0bCD4j54hXRlR/view?usp=sharing

ASIF


On Wednesday, February 10, 2021 at 10:55:02 AM UTC+11 David Shteynberg 
wrote:

> It appears you forgot to include the _DECOY version of the database.  Can 
> you check?
>
> On Tue, Feb 9, 2021 at 3:27 PM Asif Ahmed <kh.asif...@gmail.com> wrote:
>
>> Hi David,
>>
>> In my sample- N15 fed (heavy) female fly mated with N14 (normal) male 
>> fly, after mating, I dissected the female reproductive organs and process 
>> the sample using S-trap kit. 
>> So, "theoretically" in the mated female reproductive tract proteome, 
>> there would be plenty of female proteins (which would be N15) and a tiny 
>> amount of male proteins (N14 proteins).
>> Our aim is to identify male-originated proteins from the samples and for 
>> now, I just focused on normal search rather than N15 labelling search.
>> The protocol worked well for PD's SequestHT, Comet and Tandem search 
>> giving ~150 hits, and now trying to add MsGf+ in the analysis.w
>> For the database, we are using trinity assembly of male reproductive 
>> organ RNAseq, made a 6 frame translation of the assembly and add decoys 
>> (with prefix of DECOY_ ).
>>
>> For peptide prophet in petunia, I used the following parameters, as shown 
>> in the tutorial (not any unusual settings at all).
>>
>> *Use accurate mass binning, using PPM,  *
>> *Use decoy hits to pin down the negative distribution. Decoy Protein 
>> names begin with: DECOY_,  *
>> *Use Non-parametric model and *
>> *Report decoy hits with a computed probability*
>>
>> Please find the datasets containing:
>> Thermo RAW data file (201010_P31528_Sample_S1_QE_HFX_HpH_7_5p2.raw), 
>> mzML file (201010_P31528_Sample_S1_QE_HFX_HpH_7_5p2.mzML), 
>> mzid file with conf (asiftest_instrument2_S1.mzid and MSGFPlus_conf.txt) 
>> , 
>> Trinity database fasta file (with decoy), and resulted file from peptide 
>> prophet (MsGF_inst1_interact.ipro.pep.xml).
>>
>>
>> https://drive.google.com/file/d/1rULaUtY9j2Ke7N6Z_hIa_a_JyY3admvj/view?usp=sharing
>>
>> ASIF
>>
>>
>> On Wednesday, February 10, 2021 at 8:48:19 AM UTC+11 David Shteynberg 
>> wrote:
>>
>>> You can compress the directory and post your dataset in the cloud and I 
>>> will pull it down.   Perhaps you can start with your search parameters.  
>>> N15 labelling creates mass-shifts on every amino acid, how are you setting 
>>> these?  What PeptideProphet options are you using?  Any unusual options you 
>>> are setting to get this data to process?
>>>
>>> Thanks,
>>> -David
>>>
>>>
>>> On Tue, Feb 9, 2021 at 1:29 PM Asif Ahmed <kh.asif...@gmail.com> wrote:
>>>
>>>> Hi David, 
>>>>
>>>> Thanks for your reply and appreciate  your interpretation. 
>>>>
>>>> How can i share the dataset with you? I assume you might need the mzXML 
>>>> file (~1.2gb), mzid file (/pepxml file) and the database file?
>>>>
>>>> Asif
>>>>
>>>> On Wed, 10 Feb 2021 at 5:43 am, 'David Shteynberg' via spctools-discuss 
>>>> <spctools...@googlegroups.com> wrote:
>>>>
>>>>> Hello Asif,
>>>>>
>>>>> Unfortunately this analysis tells me that the DECOY-estimated FDR 
>>>>> (error rate) is about 50%-60% amongst the highest scoring proteins in 
>>>>> this 
>>>>> analysis.  I don't believe these are "acceptable" results.  The problem 
>>>>> is 
>>>>> likely somewhere upstream of the ProteinProphet analysis, I cannot 
>>>>> exactly 
>>>>> tell without seeing more of the dataset. 
>>>>>
>>>>> Best,
>>>>> -David 
>>>>>
>>>>> On Tue, Feb 9, 2021, 5:00 AM Asif Ahmed <kh.asif...@gmail.com> wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> I ran a MSgf+ search (with decoy) for my samples (a mixture of N14 
>>>>>> and N15 proteins, want to detect N14 proteins in the sample) converted 
>>>>>> resulted .mzid file to pepXML using IDconvert, changed the paths using 
>>>>>> "update path" and run Peptideprophet *(Use accurate mass binning, 
>>>>>> using PPM ,  Use decoy hits to pin down the negative distribution ,  
>>>>>> Decoy 
>>>>>> Protein names begin with: DECOY_,  Use Non-parametric model and report 
>>>>>> decoy hits)*  and iprophet and protein prophet combined (as default 
>>>>>> settings) in Petunia. 
>>>>>>
>>>>>> The run went well without any error, but the models of "Learned NSP 
>>>>>> distribution" as well as others are showing some abnormality. Can you 
>>>>>> advise me, based on the fitted models, can I can accept the result at 
>>>>>> 0.99 
>>>>>> to 1 probability?
>>>>>>
>>>>>> ASIF 
>>>>>>
>>>>>> [image: msgf1.PNG]
>>>>>>
>>>>>> [image: msgf2.PNG]
>>>>>>
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>>>>> .
>>>>>
>>>> -- 
>>>> *Khandaker Asif Ahmed*
>>>> PhD Student| Applied BioSciences, Macquarie University, NSW, Australia
>>>> Postgraduate Research Student| CSIRO Land and Water Flagship, Black 
>>>> Mountain, ACT, Australia
>>>> *Address:* Room No: S1.03, Building No: 101, CSIRO Clunies Ross 
>>>> Street, Black Mountain, ACT 2601, Australia
>>>> *Alternative Email:* khandaker...@csiro.au 
>>>> <http://khandakerasif.ah...@csiro.au/>; 
>>>> khandaker-...@students.mq.edu.au. 
>>>> *Mobile:* (+61)0434018803 <+61%20434%20018%20803>, *Skype ID:* 
>>>> kh.asifratul
>>>> Linkedin <https://www.linkedin.com/in/khandaker-asif-ahmed-24b461115/>
>>>>  | ResearchGate 
>>>> <https://www.researchgate.net/profile/Khandaker_Asif_Ahmed> | Google 
>>>> Scholar 
>>>> <https://scholar.google.com.au/citations?user=rUJ9DVAAAAAJ&hl=en>
>>>>
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