
heyang responded: 
20210922 
Forgot to mention version of Skyline, it is 21.1.0.146


Nick Shulman responded: 
20210922 
If you train an mProphet model, and use the model to pick peaks ("Refine > Reintegrate"), then you can find the "Detection ZScore" and Detection Q Value" in the document grid.
There are other scenarios where you might get a qvalue in there without using an mProphet model. For instance, if you have an EncyclopeDIA library, Skyline will read the score from the .elib file and display that value in the "Detection Q Value" column.
The Zscore has something to do with number of standard deviations. For this reason, it is a very simple formula to go from the Zscore to the pvalue (or maybe it's a simple formula to go from Zscore to qvalue I can't remember). Like a zscore of 2 corresponds to the 95% confidence interval which means a pvalue of 0.95. (I might have even gotten those example numbers wrong).
Yes, you can delete the redundant library. Skyline looks in the redundant library in order to give you a choice of spectra to look at in the Library Match window. Skyline only ever looks at the "best" spectrum when deciding which transitions to add to the document, and the best spectrum is stored in the regular .blib file. If you delete the .redundant.blib file, the only place you will notice a difference is the Library Match window.
 Nick 

Brendan MacLean responded: 
20210922 
Yes, you can easily calculate an unadjusted p value from a z score. In R, the function to use is pnorm(). So, as described by Nick, a range of +/ 2 SDs is roughly a 95% confidence interval with 2.5% of the distribution below 2 and above 2.
You can see that with pnorm() as follows:
> pnorm(2)
[1] 0.9772499
> pnorm(2)
[1] 0.02275013
Though, +/ 1.96 is closer to the true value:
> pnorm(1.96)
[1] 0.9750021
> pnorm(1.96)
[1] 0.0249979
However, with multiple hypothesis testing like mProphet it is not generally acceptable to mention the unadjusted p value. Instead, you want the q value, which is an "adjusted p value" meaning that it refers to the falsediscovery rate of the entire set, while the unadjusted p value is only acceptable to use in a controled experiment with a single welldefined test.
So, you really want to use the "Detection Q Value" and "Detection Z Score" and avoid talking about the p value you can easily get from pnorm(Detection Z Score).
Hope this makes sense and helps to clarify Nick's response.
Brendan
P.S.  The redundant library can also give you the ability to add to an existing spectral library. Whereas, if you only have the nonredundant library that is a fixed artifact to which you cannot add new data. I agree with Nick, though, that in many cases you don't really care about the uses of the redundant library and you can delete it without harmful impact. 

heyang responded: 
20210922 
Thank you, Nick.
I also have another question about retention time calibration. In attached Skyline menu file which suggest use ms/ms ID time from DDA data (page 15). Is this good enough or we need to do rt calibration for every time?
Thanks,
Heyi 


heyang responded: 
20210922 
Thank you very much, Brendan for your explanation. Heyi 

heyang responded: 
20210924 
Hi Brendon and Nick,
More question about Detection Q value and Z score. Do you have detailed instruction about these two score for beginner? For a beginner to quick check their data, what are threshold of values for 2 scores? For Z score, 3 and 3 are the same significant? Also I processed 30 samples in a batch mode. Looks same peptide from different sample have same Q value, but different Z score. Is this right?
Best,
Heyi 


