You'll find the latest release candidate (RC4) in:

https://sourceforge.net/projects/sashimi/files/Trans-Proteomic%20Pipeline%20%28TPP%29/TPP%20v0.0%20%28Development%29/

Since I don't expect any more changes this should be effectively 4.7.

-Joe



On Tue, Feb 18, 2014 at 10:28 PM, Robert Jones <[email protected]>wrote:

> Bjorn,
>
> Thank you so very much that was extremely helpful! I'll be well on my way
> to finishing my analysis.
>
> -Robert M Jones
>
>
> On Tuesday, February 18, 2014 6:45:24 AM UTC-7, Bjorn wrote:
>>
>> Hi,
>> As far as I understand it, the TPP uses a mixture model-based approach to
>> determine posterior probabilities and it then uses these probabilities to
>> estimate the FDR. This can be done with or without the use of a decoy
>> database. However, when using some of the more sophisticated options (like
>> non-parametric modelling), you will need a decoy database to help the
>> modelling algorithms pin down the negative distribution. Also, when the
>> data is of not so excellent quality, the decoys can help make a better
>> distinction between good and bad identifications.
>>
>> After the analysis with ProteinProphet, you get something like this in
>> the ProteinProphet window:
>>
>> Prob Sens FPER Corr  Incorr
>> 0.00 1.000 0.930 217 2874
>> 0.10 1.000 0.337 217 110
>> 0.20 1.000 0.337 217 110
>> 0.30 0.915 0.216 198 55
>> 0.40 0.865 0.152 187 34
>> 0.50 0.816 0.102 177 20
>> 0.60 0.777 0.074 168 14
>> 0.70 0.747 0.058 162 10
>> 0.80 0.647 0.019 140 3
>> 0.90 0.608 0.010 132 1
>> 0.95 0.569 0.005 123 1
>> 0.96 0.547 0.004 119 0
>> 0.97 0.529 0.003 115 0
>> 0.98 0.507 0.002 110 0
>> 0.99 0.470 0.001 102 0
>> 1.00 0.152 0.000 33 0
>>
>> The FPER is your FDR, so if you decide to set it at 1%, you notice that
>> this corresponds with a probability cut off of 0.90. Now, in your protein
>> list, you accept all proteins with a prob. of 0.09 or higher, which is
>> estimated to be 132 correct ones and 1 incorrect protein. Everything below
>> is discarded.
>>
>> I found lots of info in the following papers (esp. the last paper).
>> Hope this helps!
>> Cheers,
>> Bjorn
>>
>> [1] Choi, H., Fermin, D., and Nesvizhskii, A. I. Significance analysis of
>> spectral count data in label-free shotgun proteomics. Mol. Cell. Proteomics
>> 7, 12 (2008), 2373-2385.
>>
>> [2] Choi, H., Ghosh, D., and Nesvizhskii, A. I. Statistical validation of
>> peptide identifications in large-scale proteomics using the target-decoy
>> database search strategy and flexible mixture modeling. J. Proteome Res. 7,
>> 1 (2008), 286-292.
>>
>> [3] Choi, H., and Nesvizhskii, A. I. False discovery rates and related
>> statistical concepts in mass spectrometry-based proteomics. J. Proteome
>> Res. 7, 1 (2008), 47-50.
>>
>> [4] Choi, H., and Nesvizhskii, A. I. Semisupervised model-based
>> validation of peptide identifications in mass spectrometry-based
>> proteomics. J. Proteome Res. 7, 1 (2008), 254-265.
>>
>> [5] Deutsch, E. W., Mendoza, L., Shteynberg, D., Farrah, T., Lam, H.,
>> Tasman, N., Sun, Z., Nilsson, E., Pratt, B., Prazen, B., Eng, J. K.,
>> Martin, D. B., Nesvizhskii, A. I., and Aebersold, R. A guided tour of the
>> Trans-Proteomic Pipeline. Proteomics 10, 6 (2010), 1150-1159.
>>
>> [6] Keller, A., Nesvizhskii, A. I., Kolker, E., and Aebersold, R.
>> Empirical statistical model to estimate the accuracy of peptide
>> identifications made by MS/MS and database search. Anal. Chem. 74, 20
>> (2002), 5383-5392.
>>
>> [7] Nesvizhskii, A. I. A survey of computational methods and error rate
>> estimation procedures for peptide and protein identification in shotgun
>> proteomics. J. Proteomics 73, 11 (2010), 2092-2123.
>>
>  --
> You received this message because you are subscribed to the Google Groups
> "spctools-discuss" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to [email protected].
> To post to this group, send email to [email protected].
> Visit this group at http://groups.google.com/group/spctools-discuss.
> For more options, visit https://groups.google.com/groups/opt_out.
>



-- 
Joe Slagel
Institute for Systems Biology
[email protected]
(206) 732-1362

-- 
You received this message because you are subscribed to the Google Groups 
"spctools-discuss" group.
To unsubscribe from this group and stop receiving emails from it, send an email 
to [email protected].
To post to this group, send email to [email protected].
Visit this group at http://groups.google.com/group/spctools-discuss.
For more options, visit https://groups.google.com/groups/opt_out.

Reply via email to