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webinar_2021-03 [2021/03/19 09:49] – cctbx.python -> ccp4-python malywebinar_2021-03 [2021/03/24 10:09] (current) – video maly
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   - Short tutorial. [[https://pairef.fjfi.cvut.cz/docs/pairef_poli_webinar/PAIREF_webinar_poli.zip|Download the archive with the data]].   - Short tutorial. [[https://pairef.fjfi.cvut.cz/docs/pairef_poli_webinar/PAIREF_webinar_poli.zip|Download the archive with the data]].
   - Discussion.   - Discussion.
 +
 +[[https://pairef.fjfi.cvut.cz/docs/pairef_poli_webinar/PAIREF_webinar_2021-03.pdf|Download these webinar instructions in PDF]]
 +
 +==== Video recording from the webinar ====
 +
 +[[https://pairef.fjfi.cvut.cz/docs/pairef_poli_webinar/PAIREF_webinar_23Mar2021_.mp4|{{ ::pairef_webinar_2021-03_video.gif |}}]]
 +
  
 ===== Tutorial ===== ===== Tutorial =====
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 {{:ccp4console.gif?nolink|}} {{:phenix_command_prompt.gif?nolink|}} {{:ccp4console.gif?nolink|}} {{:phenix_command_prompt.gif?nolink|}}
  
-Now execute the following command that installs PAIREF on your computer: +Now execute the following commands that install PAIREF into CCP4 environment on your computer: 
-<code>ccp4-python -m pip install pairef --no-deps --upgrade --user</code>+<code> 
 +ccp4-python -m ensurepip --user 
 +ccp4-python -m pip install pairef --no-deps --upgrade --user 
 +</code>
  
 If the installation was not successful, please go through the section [[https://pairef.fjfi.cvut.cz/docs/installation.html#troubleshooting|Installation - Troubleshooting]] in our documentation. If the installation was not successful, please go through the section [[https://pairef.fjfi.cvut.cz/docs/installation.html#troubleshooting|Installation - Troubleshooting]] in our documentation.
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 The first thing that should be checked is whether the refinements have converged. Scroll at the very bottom of page, here you can see plots of Rwork and Rfree vs. refinement cycle. We can conclude that all the refinements have converged. The first thing that should be checked is whether the refinements have converged. Scroll at the very bottom of page, here you can see plots of Rwork and Rfree vs. refinement cycle. We can conclude that all the refinements have converged.
  
-Rfree decreased after the addition of shells 2.3-2.10 Å and 2.1-2.0 Å.+Rfree decreased after the addition of shells 2.3-2.10 Å and 2.1-2.0 Å:
  
 {{ :poli_webinar_r-values.png?nolink |}} {{ :poli_webinar_r-values.png?nolink |}}
  
-Since a perfect model gives an R value of 0.42 against random data (i.e. pure noise) – assuming non-tNCS (translational non-crystallographic symmetry) data from a non-twinned crystal ((Evans, P. R. & Murshudov, G. N. (2013). Acta Cryst. D69, 1204-1214.)) – a higher R value in the (current) high-resolution shell indicates either the involvement of high-resolution data without information content (the data are even worse than noise), or poor quality of the model, or the presence of tNCS. This is indicated for the shell  2.0-1.9 Å.+Since a perfect model gives an R-value of 0.42 against random data (i.e. pure noise) – assuming non-tNCS (translational non-crystallographic symmetry) data from a non-twinned crystal ((Evans, P. R. & Murshudov, G. N. (2013). Acta Cryst. D69, 1204-1214.)) – a higher R-value in the (current) high-resolution shell indicates either the involvement of high-resolution data without information content (the data are even worse than noise), or poor quality of the model, or the presence of tNCS. This is indicated for the shell  2.0-1.9 Å.
 {{ :poli_webinar_rfree.png?nolink |}} {{ :poli_webinar_rfree.png?nolink |}}
  
-CC* is higher than CCwork in whole resolution range (except the shell 2.0-1.9 Å where CC* is undefined due to negative CC1/2. No overfitting was indicated.+CC* a model-independent measure of noise is in the diffraction data. CC* is higher than CCwork in whole resolution range (except the shell 2.0-1.9 Å where CC* is undefined due to negative CC1/2. Thus, the overfitting was not indicated. To access overfitting, it is not needed to test set, so the comparison of CC* with CCwork is much better then with CCfree as CCwork is calculated on more data.
 {{ :poli_webinar_ccwork.png?nolink |}} {{ :poli_webinar_ccwork.png?nolink |}}
  
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 07      2.10   2.00  49772   4021   12.38  98.51       0.3     0.1   16.989   17.721    4.963   0.027   0.008   0.2293 07      2.10   2.00  49772   4021   12.38  98.51       0.3     0.1   16.989   17.721    4.963   0.027   0.008   0.2293
 08      2.00   1.90  35920   4046    8.88  81.18       0.1     0.0   41.435   43.993   14.417  -0.132  -0.016   N/A</code> 08      2.00   1.90  35920   4046    8.88  81.18       0.1     0.0   41.435   43.993   14.417  -0.132  -0.016   N/A</code>
 +
 +===== Contact =====
 +
 +In case of any questions or problems, please do not hesitate and write us: [[martin.maly@fjfi.cvut.cz]].
 +
 +===== Further reading =====
 +
 +  * [[https://doi.org/10.1107/S2052252520005916|Paired refinement under the control of PAIREF. M. Maly, K. Diederichs, J. Dohnalek, P. Kolenko (2020) IUCrJ 7]] 
 +  * More information about //PAIREF// settings and possibilities are explained in the [[https://pairef.fjfi.cvut.cz/docs/|documentation]].
 +
 +  * Linking crystallographic model and data quality. P.A. Karplus & K. Diederichs (2012) Science 336:1030–3
 +  * Assessing and maximizing data quality in macromolecular crystallography. P.A. Karplus & K. Diederichs (2015) Cur. Op. in Str. Biology 34:60–68
 +  * Better models by discarding data? P.A. Karplus & K. Diederichs (2013) Acta Cryst. D59:1215–1222
 +