Difference between revisions of "2017 prime tutorial"

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Line 38: Line 38:
 
     sigma_min = 1.5
 
     sigma_min = 1.5
 
     partiality_min = 0.1
 
     partiality_min = 0.1
 +
  allparams {
 +
    flag_on = True
 +
    d_min = 2.5
 +
    d_max = 20
 +
    sigma_min = 1.5
 +
    partiality_min = 0.1
 +
    uc_tolerance = 5
 +
  }
 
  }
 
  }

Revision as of 18:13, 14 February 2017

Post-refine and Merge Sample Data Set with PRIME (2017 Tutorial)

In this tutorial, we will work on the integration results from the first of Tutorial 2 (Myoglobin Data). Before proceeding to running the program, we'll consider making the input file for PRIME based on the situation of this data set.

Generating input file

PRIME input files contain information necessary for successful post-refinement and merging steps. You can access and review the list of input parameters by running prime.run or prime.run -h to view the description of these parameters. For this tutorial we'll start building in from the start.

  • Location of integration results

In this case, we know the location where the integration results (pickle files) are. We can then set,

data = /net/viper/raid1/mu238/XfelProject/dials17/extracted

Note that you supply data as a multiple arguments. The value of the parameter can be a file containing list of integration results, a folder, or a wildcard argument.

  • Unit cell information

You can obtain the mean (or median) unit-cell dimensions from either IOTA or DIALS. In case of IOTA, prime .phil file is auto generated and this information is readily available in there. For n_residues, enter number of residues in asymmetric unit of your molecule.

target_unit_cell = 91.7 91.7 46 90 90 120
target_space_group = P6
n_residues = 128
  • Detector information
pixel_size_mm = 0.172
  • Post-refinement and Scaling information

This is where you specify the optimal resolution cutoffs for post-refinement and merging. Note that when running for the first time on you newly collected data, you can choose the "expected" values (resolution which you see the spots at the corner or on the edge. You can then adjust these parameters when analyzing merging statistics depending on the values in the high resolution shells and rerun the program again.

scale {
   d_min = 2.5
   d_max = 20
   sigma_min = 1.5
}
postref {
  scale {
    d_min = 2.5
    d_max = 20
    sigma_min = 1.5
    partiality_min = 0.1
  allparams {
    flag_on = True
    d_min = 2.5
    d_max = 20
    sigma_min = 1.5
    partiality_min = 0.1
    uc_tolerance = 5
  }
}