|
| Python-based Hierarchical ENvironment for Integrated Xtallography |
| Documentation Home |
Automated structure solution with AutoSol
Author(s)
PurposeThe AutoSol Wizard uses HYSS, SOLVE, Phaser, RESOLVE, xtriage and phenix.refine to solve a structure and generate experimental phases with the MAD, MIR, SIR, or SAD methods. The Wizard begins with datafiles (.sca, .hkl, etc) containing amplitidues (or intensities) of structure factors, identifies heavy-atom sites, calculates phases, carries out density modification and NCS identification, and builds and refines a preliminary model. UsageThe AutoSol Wizard can be run from the PHENIX GUI, from the command-line, and from parameters files. All three versions are identical except in the way that they take commands from the user. See Using the PHENIX Wizards for details of how to run a Wizard. The command-line version will be described here, except for MIR and multiple datasets, which can only be run with the GUI or with a parameters file. The GUI is documented separately. How the AutoSol Wizard worksThe basic steps that the AutoSol Wizard carries out are described below. They are: Setting up inputs, Analyzing and scaling the data, Finding heavy-atom (anomalously-scattering atom) sites, Scoring of heavy-atom solutions, Phasing, Density modification (including NCS averaging), and Preliminary model-building and refinement. The data for structure solution are grouped into Datasets and solutions are stored in Solution objects. Setting up inputsThe AutoSol Wizard expects the following basic information: (1) a datafile name (w1.sca or data=w1.sca) (2) a sequence file (seq.dat or seq_file=seq.dat) (3) how many sites to look for (2 or sites=2) (4) what the anomalously-scattering atom is (Se or atom_type=Se) (5) It is helpful to add the wavelength and f_prime and f_double_prime for each wavelength or derivative that you have as well You can also specify many other parameters, including resolution, number of sites, whether to search in a thorough or quick fashion, how thoroughly to build a model, etc. If you have a heavy-atom solution from a previous run or another approach, you can read it in directly as well. Your parameters can be specified on the command-line, using a GUI, or by editing a parameters file (examples below). Datafile formats in AutoSolAutoSol will accept the following formats of data:
The data from any of these formats will be converted to amplitudes (F+ , sigF+, and F-, sigF-) internally. For the best scaling results, you should supply all scalepack unmerged original index files or all mtz unmerged files. If all the files are scalepack unmerged original index or all the files are mtz unmerged and no anisotropy correction is applied, then SOLVE local scaling will be applied to the data prior to merging and averaging equivalent reflections. In all other cases equivalent reflections will be averaged prior to scaling, so that the scaling may not be as effective at removing systematic errors due to absorption or other effects. Datasets and Solutions in AutoSolAutoSol breaks down the data for a structure solution into datasets, where a dataset is a set of data that corresponds to a single set of heavy-atom sites. An entire MAD dataset is a single dataset. An MIR structure solution consists of several datasets (one for each native-derivative combination). A MAD + SIR structure has one dataset for the MAD data and a second dataset for the SIR data. The heavy-atom sites for each dataset are found separately (but using difference Fouriers from any previously-solved datasets to help). In the phasing step all the information from all datasets is merged into a single set of phases. The AutoSol wizard uses a "Solution" object to keep track of heavy-atom solutions and the phased datasets that go with them. There are two types of Solutions: those which consist of a single dataset (Primary Solutions) and those that are combinations of datasets (Composite Solutions). "Primary" Solutions have information on the datafiles that were part of the dataset and on the heavy-atom sites for this dataset. Composite Solutions are simply sets of Primary Solutions, with associated origin shifts. The hand of the heavy-atom or anomalously-scattering atom substructure is part of a Solution, so if you have two datatsets, each with two Solutions related by inversion, then AutoSol would normally construct four different Composite Solutions from these and score each one as described below. Analyzing and scaling the dataThe AutoSol Wizard analyzes input datasets with phenix.xtriage to identify twinning and other conditions that may require special care. The data is scaled with SOLVE. For MAD data, FA values are calculated as well. Note on anisotropy corrections: The AutoSol wizard will apply an anistropy correction and B-factor sharpening to all the raw experimental data by default (controlled by they keyword remove_aniso=True). The target overall Wilson B factor can be set with the keyword b_iso, as in b_iso=25. By default the target Wilson B will be 10 times the resolution of the data (e.g., if the resolution is 3 A then b_iso=30.), or the actual Wilson B of the data, whichever is lower. If an anisotropy correction is applied then the entire AutoSol run will be carried out with anisotropy-corrected and sharpened data. At the very end of the run the final model will be re-refined against the uncorrected refinement data and this re-refined model and the uncorrected refinement data (with freeR flags) will be written out. For the top solution this will be as overall_best.pdb and overall_best_refine_data.mtz; for all other solutions the files will be listed at the end of the log file. Finding heavy-atom (anomalously-scattering atom) sitesThe AutoSol Wizard uses HYSS to find heavy-atom sites. The result of this step is a list of possible heavy-atom solutions for a dataset. For SIR or SAD data, the isomorphous or anomalous differences, respectively are used as input to HYSS. For MAD data, the anomalous differences at each wavelength, and the FA estimates of complete heavy-atom structure factors from SOLVE are each used as separate inputs to HYSS. Each heavy-atom substructure obtained from HYSS corresponds to a potential solution. In space groups where the heavy-atom structure can be either hand, a pair of enantiomorphic solutions is saved for each run of HYSS. Running AutoSol separately in related space groupsAutoSol will check for the opposite hand of the heavy-atom solution, and at the same time it will check for the opposite hand of your space group (It will invert the heavy-atom solution from HYSS and invert the hand of the space group at the same time). Therefore you do not need to run AutoSol twice for space groups that are chiral (for example P41). The corresponding inverse space groups will be checked automatically (P43 ). If there are possibilities for your space group other than the inverse hand of the space group, then you should test them all, one at a time. For example if you were not able to measure 00l reflections in a hexagonal space group, your space group might be P6, P61, P62, P63, P64 or P65. In this case you would have to run it in P6, P61 P62 and P63 (and then P65 and P64 will be done automatically as the inverses of P61 and P62). Normally only one of these will give a plausible solution. Scoring of heavy-atom solutionsPotential heavy-atom solutions are scored based on a set of criteria (SKEW, CORR_RMS, CC_DENMOD, RFACTOR, NCS_OVERLAP,TRUNCATE, REGIONS, CONTRAST, FOM, FLATNESS, described below), using either a Bayesian estimate or a Z-score system to put all the scores on a common scale and to combine them into a single overall score. The overall scoring method chosen (BAYES-CC or Z-SCORE) is determined by the value of the keyword overall_score_method. The default is BAYES-CC. Note that for all scoring methods, the map that is being evaluated, and the estimates of map-perfect-model correlation, refer to the experimental electron density map, not the density-modified map. Bayesian CC scores (BAYES-CC). Bayesian estimates of the quality of experimental electron density maps are obtained using data from a set of previously-solved datasets. The standard scoring criteria were evaluated for 1905 potential solutions in a set of 246 MAD, SAD, and MIR datasets. As each dataset had previously been solved, the correlation between the refined model and each experimental map (CC_PERFECT) could be calculated for each solution (after offsetting the maps to account for origin differences). Histograms were tabulated of the number of instances that a scoring criterion (e.g., SKEW) had various possible values, as a function of the CC_PERFECT of the corresponding experimental map to the refined model. These histograms yield the relative probability of measuring a particular value of that scoring criterion (SKEW), given the value of CC_PERFECT. Using Bayes' rule, these probabilities can be used to estimate the relative probabilities of values of CC_PERFECT given the value of each scoring criterion for a particular electron density map. The mean estimate (BAYES-CC) is reported (multiplied x 100), with a +/-2SD estimate of the uncertainty in this estimate of CC_PERFECT. The BAYES-CC values are estimated independently for each scoring criterion used, and also from all those selected with the keyword score_type_list and not selected with the keyword skip_score_list. Z-scores (Z-SCORE). The Z-score for one criterion for a particular solution is given by, Z= (Score - mean_random_solution_score)/(SD_of_random_solution_scores)where Score is the score for this solution, mean_random_solution_score is the mean score for a solution with randomized phases, and SD_of_random_solution_scores is the standard deviation of the scores of solutions with randomized phases. To create a total score based on Z-scores, the Z-scores for each criterion are simply summed. The principal scoring criteria are: The skew (SKEW; third moment or normalized <rho**3>) of the density in an electron density map is a good measure of its quality, because a random map has a skew of zero (density histograms look like a Gaussian), while a good map has a very positive skew (density histograms very strong near zero, but many points with very high density). This criterion is used in scoring by default. Correlation of local rms density (CORR_RMS). The presence of contiguous flat solvent regions in a map was detected using the correlation coefficient of the smoothed squared electron density calculated as described above, with the same quantity calculated using half the value of the smoothing radius, yielding the correlation of rms density, r2RMS. In this way the local value of the rms density within a small local region (typically within a radius of 3 A) is compared with the local rms density in a larger local region (typically within a radius of 6 A). If there were a large, contiguous solvent region and another large contiguous region containing the macromolecule, the local rms density in the small region would be expected to be highly correlated with the rms density in the larger region. On the other hand, if the solvent region were broken up into many small flat regions, then this correlation would be expected to be smaller. Correlation of map-phased electron density map with experimentally- phased map (CC_DENMOD). The statistical density modification in RESOLVE allows the calculation of map-based phases that are (mostly) independent of the experimental phases. The phase information in statistical density modification comes from two sources: your experimental phases and maximization of the agreement of the map with expectations (such as a flat solvent region). Normally the phase probabilities from these two sources are merged together, yielding your density-modified phases. This score is calculated based on the correlation of the phase information from these two sources before combining them, and is a good indication of the quality of the experimental phases. This criterion is used in scoring by default. The R-factor for density modification (RFACTOR). Statistical density modification provides an estimate of structure factors that is (mostly) independent of the measured structure factors, so the R-factor between FC and Fobs is a good measure of the quality of experimental phases. This criterion is used in scoring by default. Non-crystallographic symmetry (NCS_OVERLAP). The presence of NCS in a map is a nearly-positive indication that the map is good, or has some correct features. The AutoSol Wizard uses symmetry in heavy-atom sites to suggest NCS, and RESOLVE identifies the actual correlation of NCS-related density for the NCS overlap score. This score is used by default if NCS is present in the Z-score method of scoring. Figure of merit (FOM). The figure of merit of phasing is a good indicator of the internal consistency of a solution. This score is not normalized by the SD of randomized phase sets (as that has no meaning; rather a standard SD=0.05 is used). This score is used by default if NCS is present in the Z-score method of scoring and in the Bayesian CC estimate method. Map correlation after truncation (TRUNCATION). Dummy atoms (the same number as estimated non-hydrogen atoms in the structure) are placed in positions of high density of the map, and a new map is calculated based on these atomic positions. The correlation of these maps is calculated after adjusting an overall B-value for the dummy atoms to maximize the correlation. A good map will show a high correlation of these maps. This score is by default not used. Number of contiguous regions per 100 A**3 comprising top 5% of density in map (REGIONS). The top 5% of points in the map are marked, and the number of contiguous regions that result are counted, and divided by the volume of the asymmetric unit, then multiplied by 100. A good map will have just a few contiguous regions at a high contour level, a poor map will have many isolated peaks. This score is by default not used. Contrast, or standard deviation of local rms density (CONTRAST). The local rms density in the map is calculated using a smoothing radius of 3 times the high-resolution cutoff (or 6 A, if less than 6A). Then the standard deviation of the local rms, normalized to the mean value of the local rms, is reported. This criteria will be high if there are regions of high local rms (the macromolecule) and separate regions of low local rms (the solvent) and low if the map is random. This score is by default not used. PhasingThe AutoSol Wizard uses Phaser to calculate experimental phases from SAD data, and SOLVE to calculate phases from MIR, MAD, and multiple-dataset cases. Density modification (including NCS averaging)The AutoSol Wizard uses RESOLVE to carry out density modification. It identifies NCS from symmetries in heavy-atom sites with RESOLVE and applies this NCS if it is present in the electron density map. Preliminary model-building and refinementThe AutoSol Wizard carries out one cycle of model-building and refinement after obtaining density-modified phases. The model-building is done with RESOLVE. The refinement is carried out with phenix.refine. Resolution limits in AutoSolThere are several resolution limits used in AutoSol. You can leave them all to default, or you can set any of them individually. Here is a list of these limits and how their default values are set: Output files from AutoSolWhen you run AutoSol the output files will be in a subdirectory with your run number: AutoSol_run_1_/ The key output files that are produced are:
How to run the AutoSol WizardRunning the AutoSol Wizard is easy. From the command-line you can type: phenix.autosol w1.sca seq.dat 2 Se f_prime=-8 f_double_prime=4.5 The AutoSol Wizard will assume that w1.sca is a datafile (because it ends in .sca and is a file) and that seq.dat is a sequence file, that there are 2 heavy-atom sites, and that the heavy-atom is Se. The f_prime and f_double_prime values are set explicitly You can also specify each of these things directly: phenix.autosol data=w1.sca seq_file=seq.dat sites=2 \ atom_type=Se f_prime=-8 f_double_prime=4.5 You can specify many more parameters as well. See the list of keywords, defaults and descriptions at the end of this page and also general information about running Wizards at Using the PHENIX Wizards for how to do this. Some of the most common parameters are: sites=3 # 3 sites sites_file=sites.pdb # ha sites in PDB or fractional xyz format atom_type=Se # Se is the heavy-atom seq_file=seq.dat # sequence file (1-aa code, separate chains with >>>>) quick=True # try to find sites quickly data=w1.sca # input datafile lambda=0.9798 # wavelength for SAD Running from a parameters fileYou can run phenix.autosol from a parameters file. This is often convenient because you can generate a default one with: phenix.autosol --show_defaults > my_autosol.effand then you can just edit this file to match your needs and run it with: phenix.autosol my_autosol.effNOTE: the autosol parameters file my_autosol.eff will have just one blank native, derivative, and wavelength. You can cut and paste them to put in as many as you want to have. Model viewing during model-building with the Coot-PHENIX interfaceThe AutoSol Wizard allows you to view the current best model that is produced by the automated model-building process. This capability is identical to the view/edit model procedure available in the AutoBuild Wizard. Normally you would use it just to view the model in AutoSol, and to view and edit a model in AutoBuild . The PHENIX-Coot interface is accessible via the command-line. When a model has been produced by the AutoSol Wizard, you can open a new window and type: phenix.autobuild cootwhich will start Coot with your current map and model. When Coot has been loaded, your map and model will be displayed along with a PHENIX-Coot Interface window. If you want, you can edit your model and then save it, giving it back to PHENIX with the button labelled something like Save model as COMM/overall_best_coot_7.pdb. This button creates the indicated file and also tells PHENIX to look for this file and to try and include the contents of the model in the building process. In AutoSol, only the main-chain atoms of the model you save are considered, and the side-chains are ignored. Ligands and solvent in the model are ignored as well. As the AutoSol Wizard continues to build new models and create new maps, you can update in the PHENIX-Coot Interface to the current best model and map with the button Update with current files from PHENIX. ExamplesSAD datasetphenix.autosol w1.sca seq.dat 2 Se lambda=0.9798The sequence file is used to estimate the solvent content of the crystal and for model-building. The wavelength (lambda) is used to look up values for f_prime and f_double_prime from a table, but if measured values are available from a fluorescence scan, these should be given in addition to the wavelength. SAD dataset specifying solvent fractionphenix.autosol w1.sca seq.dat 2 Se lambda=0.9798 \
solvent_fraction=0.45
This will force the solvent fraction to be 0.45. This illustrates a
general feature of the Wizards: they will try to estimate values of
parameters, but if you input them directly, they will use your input
values.
SAD dataset without model-buildingphenix.autosol w1.sca seq.dat 2 Se lambda=0.9798 \
build=False
This will carry out the usual structure solution, but will skip model-building
SAD dataset, building RNA instead of proteinphenix.autosol w1.sca seq.dat 2 Se lambda=0.9798 \
chain_type=RNA
This will carry out the usual structure solution, but will build an RNA
chain. For DNA, specify chain_type=DNA. You can only build one type of
chain at a time in the AutoSol Wizard. To build protein and DNA, use
the AutoBuild
Wizard and run it first with chain_type=PROTEIN, then
run it again specifying the protein
model as input_lig_file_list=proteinmodel.pdb
and with chain_type=DNA.
SAD dataset, selecting a particular dataset from an MTZ fileIf you have an input MTZ file with more than one anomalous dataset, you can type something like: phenix.autosol w1.mtz seq.dat 2 Se lambda=0.9798 \ labels='F+ SIGF+ F- SIGF-'This will carry out the usual structure solution, but will choose the input data columns based on the labels: 'F+ SIGF+ F- SIGF-' NOTE: to specify anomalous data with F+ SIGF+ F- SIGF- like this, these 4 columns must be adjacent to each other in the MTZ file with no other columns in between. FURTHER NOTE: to instead use a FAVG SIGFAVG DANO SIGDANO array in AutoSol, the data file or an input refinement file MUST also contain a separate array for FP SIGFP or I SIGI or equivalent. This is because FAVG DANO arrays are ONLY allowed as anomalous information, not as amplitudes or intensities. You can use F+ SIGF+ F- SIGF- arrays as a source of both anomalous differences and amplitudes if you want, however. If you run the AutoSol Wizard with SAD data and an MTZ file containing more than one anomalous dataset and don't tell it which one to use, all possible values of labels are printed out for you so that you can just paste the one you want in. You can also find out all the possible label strings to use by typing: phenix.autosol display_labels=w1.mtz # display all labels for w1.mtz MRSAD -- SAD dataset with an MR model; Phaser SAD phasing including the modelIf you are carrying out SAD phasing with Phaser, you can carry out a combination of molecular replacement phasing and SAD phasing (MRSAD) by adding a single new keyword to your AutoSol run: input_partpdb_file=MR.pdbIn this case the MR.pdb file will be used as a partial model in a maximum-likelihood SAD phasing calculation with Phaser to calculate phases and identify sites in Phaser, and the combined MR+SAD phases will be written out. NOTE: At the moment the AutoBuild Wizard is not equipped to use these combined phases optimally in iterative model-building, density modification and refinement, because they contain both experimental phase information and model information. It is therefore possible that the resulting phases are biased by your MR model, and that this bias will not go away during iterative model-building because it is continually fed back in. Using an MR model to find sites and as a source of phase information (method #2 for MRSAD)You can also combine MR information with SAD phases (see J. P. Schuermann and J. J. Tanner Acta Cryst. (2003). D59, 1731-1736 ) in PHENIX by running the three wizards AutoMR, AutoSol, and AutoBuild one after the other. This method does not use the partial model and the anomalous information in the SAD dataset simultaneously as the above Phaser maximum-likelihood method does. On the other hand, the phases obtained in this method are independent of the model, so that combining them afterwards does not introduce model bias. (It is not yet clear which is the better approach, so you may wish to try both.) Additionally, this approach can be used with any method for phasing. Here is a set of three simple commands to do this: First run AutoMR to find the molecular replacement solution, but don't rebuild it yet: phenix.automr gene-5.pdb peak.sca copies=1 \ RMS=1.5 mass=9800 rebuild_after_mr=FalseNow your MR solution is in AutoMR_run_1_/MR.1.pdb and phases are in AutoMR_run_1_/MR.1.mtz. Use these phases as input to AutoSol, along with some weak SAD data, still not building any new models: phenix.autosol data=peak.sca \ input_phase_file=AutoMR_run_1_/MR.1.mtz input_phase_labels="F PHIC FOM" \ seq_file=sequence.dat build=Falsenote that we have specified the data columns for F PHI and FOM in the input_phase_file. For input_phase_file you must specify all three of these (if you leave out FOM it will set it to zero). AutoSol will write an MTZ file with experimental phases to phaser_xx.mtz where xx depends on how many solutions are considered during the run. The next command for running AutoBuild you will need to edit depending on the value of xx: phenix.autobuild data=AutoSol_run_1_/phaser_2.mtz \ model=AutoMR_run_1_/MR.1.pdb seq_file=sequence.dat rebuild_in_place=FalseAutoBuild will now take the phases from your AutoSol run and combine them with model-based information from your AutoMR MR solution, and will carry out iterative density modification, model-building and refinement to rebuild your model. Note that you may wish to set rebuild_in_place=True, depending on how good your MR model is. SAD dataset, reading heavy-atom sites from a PDB file written by phenix.hyssphenix.autosol 11 Pb data=deriv.sca seq_file=seq.dat \ sites_file=deriv_hyss_consensus_model.pdb lambda=0.95This will carry out the usual structure solution process, but will read sites from deriv_hyss_consensus_model.pdb, try both hands, and carry on from there. If you know the hand of the substructure, you can fix it with have_hand=True. MAD datasetThe inputs for a MAD dataset need to specify f_prime and f_double_prime for each wavelength. You can use a parameters file "mad.eff" to input MAD data. You run it with "phenix.autosol mad.eff". Here is an example of a parameters file for a MAD dataset. You can set many additional parameters as well (see the list at the end of this document).
autosol {
seq_file = seq.dat
sites = 2
atom_type = Se
wavelength {
data = peak.sca
lambda = .9798
f_prime = -8.0
f_double_prime = 4.5
}
wavelength {
data = inf.sca
lambda = .9792
f_prime = -9.0
f_double_prime = 1.5
}
}
MAD dataset, selecting particular datasets from an MTZ fileThis is similar to the case for running a SAD analysis, selecting particular columns of data from an MTZ file. If you have an input MTZ file with more than one anomalous dataset, you can use a parameters file like the one above for MAD data, but adding information on the labels in the MTZ file that are to be chosen for each wavelength:
autosol {
seq_file = seq.dat
sites = 2
atom_type = Se
wavelength {
data = mad.mtz
lambda = .9798
f_prime = -8.0
f_double_prime = 4.5
labels='peak(+) SIGpeak(+) peak(-) SIGpeak(-)'
}
wavelength {
data = mad.mtz
lambda = .9792
f_prime = -9.0
f_double_prime = 1.5
labels='infl(+) SIGinfl(+) infl(-) SIGinfl(-)'
}
}
This will carry out the usual structure solution, but will choose the
input peak data columns based on the label keywords.
As in the SAD case, you can find out all the possible label strings to use by typing: phenix.autosol display_labels=w1.mtz # display all labels for w1.mtz SIR datasetThe standard inputs for an SIR dataset are the native and derivative, the sequence file, the heavy-atom type, and the number of sites, as well as whether to use anomalous differences (or just isomorphous differences): phenix.autosol native.data=native.sca deriv.data=deriv.sca \ atom_type=I sites=2 inano=inanoThis will set the heavy-atom type to Iodine, look for 2 sites, and include anomalous differences. You can also specify many more parameters using a parameters file. This parameters file shows some of them:
autosol {
seq_file = seq.dat
native {
data = native.sca
}
deriv {
data = pt.sca
lambda = 1.4
atom_type = Pt
f_prime = -3.0
f_double_prime = 3.5
sites = 3
}
}
SAD with more than one anomalously-scattering atomYou can tell the AutoSol wizard to look for more than one anomalously- scattering atom. Specify one atom type (Se) in the usual way. Then specify any additional ones like this if you are running AutoSol from the command line: mad_ha_add_list="Br Pt"Optionally, you can add f_prime and f_double_prime values for the additional atom types with commands like mad_ha_add_f_prime_list=" -7 -10" mad_ha_add_f_double_prime_list=" 4.2 12"but the values from table lookup should be fine. Note that there must be the same number of entries in each of these three keyword lists, if given. During phasing Phaser will try to add whichever atom types best fit the scattering from each new site. This option is available for SAD phasing only and only for a single dataset (not with SAD+MIR etc). MIR datasetIt is easiest to run an MIR dataset using a parameters file such as "mir.eff" which you then run with "phenix.autosol mir.eff". Here is an example parameters file for MIR:
autosol {
seq_file = seq.dat
native {
data = native.sca
}
deriv {
data = pt.sca
lambda = 1.4
atom_type = Pt
}
deriv {
data = ki.sca
lambda = 1.5
atom_type = I
}
}
You can enter as many derivatives as you want. If you specify a wavelength and heavy atom type then scattering factors are calculated from a table for that heavy-atom. You can instead enter scattering factors with the keywords "f_prime = -3.0 " "f_double_prime = 5.0" if you want. SIR + SAD datasetsA combination of SIR and SAD datasets (or of SAD+SAD or MIR+SAD+SAD or any other combination) is easy with a parameters file. You tell the wizard which grouping each wavelength, native, or derivative goes with with a keyword such as "group=1".
autosol {
seq_file = seq.dat
native {
group = 1
data = native.sca
}
deriv {
group = 1
data = pt.sca
lambda = 1.4
atom_type = Pt
}
wavelength {
group = 2
data = w1.sca
lambda = .9798
atom_type = Se
f_prime = -7.
f_double_prime = 4.5
}
}
The SIR and SAD datasets will be solved separately (but whichever one is solved first will use difference Fourier or anomalous difference Fourier's to locate sites for the other). Then phases will be combined by addition of Hendrickson-Lattman coefficients and the combined phases will be density modified. Possible ProblemsGeneral limitationsSpecific limitations and problems
Literature
Additional informationList of all AutoSol keywords
-------------------------------------------------------------------------------
Legend: black bold - scope names
black - parameter names
red - parameter values
blue - parameter help
blue bold - scope help
Parameter values:
* means selected parameter (where multiple choices are available)
False is No
True is Yes
None means not provided, not predefined, or left up to the program
"%3d" is a Python style formatting descriptor
-------------------------------------------------------------------------------
autosol
atom_type= None Anomalously-scattering atom type. This sets the atom_type
in all derivatives and wavelengths. Normally it is used as a
shortcut for SAD or SIR cases.
lambda= None Wavelength (A). This sets the wavelength value in all
derivatives and wavelengths. Normally it is used as a shortcut for
SAD or SIR cases.
f_prime= None F-prime value. This sets the f_prime value in all derivatives
and wavelengths. Normally it is used as a shortcut for SAD or SIR
cases.
f_double_prime= None F-double-prime value. This sets the f_double_prime
value in all derivatives and wavelengths. Normally it is
used as a shortcut for SAD or SIR cases.
wavelength_name= peak inf high low remote Optional name of wavelength for
SAD data. This sets the name in all wavelengths. Normally
it is used as a shortcut for SAD cases.
sites= None Number of heavy-atom sites. This sets the number of sites in
all derivatives and wavelengths. Normally it is used as a shortcut
for SAD or SIR cases.
sites_file= None PDB or plain-text file with ha sites. This sets the sites
in all derivatives and wavelengths. Normally it is used as a
shortcut for SAD or SIR cases.
seq_file= Auto Text file with 1-letter code of protein sequence NOTES: 1.
lines starting with > are ignored and separate chains 2. FASTA
format is fine 3. If there are multiple copies of a chain, just
enter one copy. 4. If you enter a PDB file for rebuilding and it
has the sequence you want, then the sequence file is not
necessary. NOTE: You can also enter the name of a PDB file that
contains SEQRES records, and the sequence from the SEQRES records
will be read, written to seq_from_seqres_records.dat, and used as
your input sequence. If you have a duplex DNA, enter each strand
as a separate chain.
quick= None Run everything quickly (Same as thoroughness=quick)
data= None Shortcut for name of datafile (SAD data only. For SIR use
"native.data=native.sca" and
"deriv.data=deriv.sca". For MIR and MAD use a parameters
file and specify data under "native" and " deriv"
or for "wavelength") NOTE: For command_line input it is
easiest if each wavelength of data is in a separate data file with
obvious data columns. File types that are easy to read include
Scalepack sca files , CNS hkl files, mtz files with just one
wavelength of data, or just native or just derivative. In this case
the Wizard can read your data without further information. If you
have a datafile with many columns, you can use the "labels"
keyword to specify which data columns to read. (It may be easier in
some cases to use the GUI or to split it with
phenix.reflection_file_converter first, however.)
labels= None Shortcut for specification string for data labels (SAD data
only). Only necessary if the wizard does not automatically choose
the correct set of data from your file For SIR use
"native.labels" and "deriv.labels". For MIR and
MAD use a parameters file and specify labels under
"native" and " deriv" NOTE: To find out what
the appropriate strings are, type "phenix.autosol
display_labels=your-datafile-here.mtz"
crystal_info
unit_cell= None Enter cell parameter (a b c alpha beta gamma)
space_group= None Space Group symbol (i.e., C2221 or C 2 2 21)
solvent_fraction= None Solvent fraction in crystals (0 to 1). This is
normally set automatically from the number of NCS
copies and the sequence.
chain_type= *Auto PROTEIN DNA RNA You can specify whether to build
protein, DNA, or RNA chains. At present you can only build
one of these in a single run. If you have both DNA and
protein, build one first, then run AutoBuild again,
supplying the prebuilt model in the
"input_lig_file_list" and build the other. NOTE:
default for this keyword is Auto, which means "carry
out normal process to guess this keyword". The process
is to look at the sequence file and/or input pdb file to see
what the chain type is. If there are more than one type, the
type with the larger number of residues is guessed. If you
want to force the chain_type, then set it to PROTEIN RNA or
DNA.
resolution= 0 High-resolution limit. Used as resolution limit for
density modification and as general default high-resolution
limit. If resolution_build or refinement_resolution are set
then they override this for model-building or refinement. If
overall_resolution is set then data beyond that resolution
is ignored completely. Zero means keep everything.
change_sg= False You can change the space group. In AutoSol the Wizard
will use ImportRawData and let you specify the sg and cell.
In AutoMR the wizard will give you an entry form to specify
them. NOTE: This only applies when reading in new datasets.
It does nothing when changed after datasets are read in.
residues= None Number of amino acid residues in the au (or equivalent)
sequence= None Plain text containing 1-letter code of protein sequence
Same as seq_file except the sequence is read directly, not
from a file. If both are given, seq_file is ignored.
input_files
cif_def_file_list= None You can enter any number of CIF definition
files. These are normally used to tell phenix.refine
about the geometry of a ligand or unusual residue.
You usually will use these in combination with
"PDB file with metals/ligands" (keyword
"input_lig_file_list" ) which allows you to
attach the contents of any PDB file you like to your
model just before it gets refined. You can use
phenix.elbow to generate these if you do not have a
CIF file and one is requested by phenix.refine
group_labels_list= None For command-line and script running of AutoSol,
you may wish to use keywords to specify which set of
data columns to be used from an MTZ or other file
type with multiple datasets. (From the GUI, it is
easy because you are prompted with the column
labels). You can do this by specifying a string that
identifies which dataset to include. All allowed
values of this identification string will be written
out any time AutoSol is run on this dataset like
this: NOTE: To specify a particular set of data you
can specify one of the following (this example is for
MAD data, specifying data for peak wavelength): ...:
peak.labels='F SIGF DANO SIGDANO' peak.labels='F(+)
SIGF(+) F(-) SIGF(-)' You can then use one of the
above commands on the command-line to identify the
dataset of interest. If you want to use a script
instead, you can specify N files in your
input_data_file_list, and then specify N values for
group_labels_list like this: group_labels_list
'F,SIGF,DANO,SIGDANO' 'F(+),SIGF(+),F(-),SIGF(-)'
This will take 'F,SIGF,DANO,SIGDANO' as the data for
datafile 1 and 'F(+),SIGF(+),F(-),SIGF(-)' for
datafile 2 You can identify one dataset from each
input file in this way. If you want more than one,
then please use phenix.reflection_file_converter to
split your input file, or else use the GUI version of
AutoSol in which you can select any subset of the
data that you wish.
input_file_list= None Normally not used. Use "data=" or
"wavelength.data=" or
"native.data=" or "deriv.data="
instead.
input_phase_file= None MTZ data file with FC PHIC or equivalent to use
for finding heavy-atom sites with difference Fourier
methods.
input_phase_labels= None Labels for FC and PHIC for data file with FC
PHIC or equivalent to use for finding heavy-atom
sites with difference Fourier methods.
input_refinement_file= None Data file to use for refinement. The data in
this file should not be corrected for anisotropy.
It will be combined with experimental phase
information for refinement. If you leave this
blank, then the output of phasing will be used in
refinement (see below). If no anisotropy
correction is applied to the data you do not need
to specify a datafile for refinement. If an
anisotropy correction is applied to the data
files, then you must enter a datafile for
refinement if you want to refine your model. (See
"remove_aniso" for specifying whether
an anisotropy correction is applied. In most
cases it is not.) If an anisotropy correction is
applied and no refinement datafile is supplied,
then no refinement will be carried out in the
model-building step. You can choose any of your
datafiles to be the refinement file, or a native
that is not part of the datasets for structure
solution. If there are more than one dataset you
will be asked each time for a refinement file,
but only the last one will be used. Any standard
format is fine; normally only F and sigF will be
used. Bijvoet pairs and duplicates will be
averaged. If an mtz file is provided then a free
R flag can be read in as well. If you do not
provide a refinement file then the structure
factors from the phasing step will be used in
refinement. This is normally satisfactory for SAD
data and MIR data. For MAD data you may wish to
supply a refinement file because the structure
factors from phasing are a combination of data
from different wavelengths of data. It is better
if you choose your best wavelength of data for
refinement.
input_refinement_labels= None Labels for input refinement file columns
(FP SIGFP FreeR_flag)
input_seq_file= Auto Normally not used. Use instead "seq_file"
refine_eff_file_list= None You can enter any number of refinement
parameter files. These are normally used to tell
phenix.refine defaults to apply, as well as
creating specialized definitions such as unusual
amino acid residues and linkages. These parameters
override the normal phenix.refine defaults. They
themselves can be overridden by parameters set by
the Wizard and by you, controlling the Wizard.
NOTE: Any parameters set by AutoBuild directly
(such as number_of_macro_cycles, high_resolution,
etc...) will not be taken from this parameters
file. This is useful only for adding extra
parameters not normally set by AutoBuild.
wavelength Enter a SAD or MAD dataset by filling in information for one or
more wavelengths. You can cut and paste an entire wavelength
section and enter as many as you like. If you have multiple
datasets (i.e., MIR+MAD) then group them using the
"group" keyword.
wavelength_name= peak inf high low remote Optionally indicate if this is
the peak, inflection point, high energy remote or low
energy remote or remote
data= None Datafile for this wavelength.
labels= None Specification string for data labels for peak wavelength.
Only necessary if the wizard does not automatically choose the
correct set of data from your file To find out what the
appropriate strings are, type "phenix.autosol
display_labels=your-datafile-here.mtz"
atom_type= None Anomalously-scattering atom type. You only need to
specify this for one of the wavelengths in MAD datasets.
NOTE: if you want Phaser to add additional heavy-atoms of
other types, you can specify them with mad_ha_add_list.
lambda= None wavelength (A). If you supply an atom_type and lambda then
if you do not supply f_prime and f_double_prime a guess will be
made for them from a table.
res_hyss= None resolution for running HYSS for this wavelength/deriv
res_eval= None resolution for evaluation of solutions for this
wavelength/deriv
f_prime= None F-prime value for this wavelength. It is best to supply it
if you know it.
f_double_prime= None F-double_prime value for this wavelength. It is
best to supply it if you know it.
sites= None Number of anomalously-scattering sites for this wavelength
You only need to specify this for one wavelength. If you have
only MAD data you can also just specify "sites=2"
sites_file= None PDB or plain-text file with heavy-atom sites. The sites
will be taken from this file if supplied
group= 1 Phasing group(s) this wavelength is associated with (Relevant
in cases where you have 2 MAD datasets or MAD+SAD or MAD+MIR
etc...)
added_wavelength= False Used internally to flag if this wavelength was
added automatically
ignore= False Ignore this wavelength of data
native Enter an MIR or SIR dataset by filling in information for a native
and one or more derivatives. You can cut and paste these sections
and enter as many as you like. If you have multiple datasets (i.e.,
MIR+MAD) then group them using the "group" keyword.
data= None Datafile for native
labels= None Specification string for data labels for native. Only
necessary if the wizard does not automatically choose the
correct set of data from your file To find out what the
appropriate strings are, type "phenix.autosol
display_labels=your-datafile-here.mtz "
lambda= None wavelength (A) (Not used, for your reference only).
group= 1 Phasing group(s) this native is associated with (Relevant in
cases where you have more than one group of native+derivs or you
have MIR + MAD or SAD)
added_native= False Used internally to flag if this native was added
automatically
ignore= False Ignore this native data
deriv Enter an MIR or SIR dataset by filling in information for a native
and one or more derivatives. You can cut and paste these sections and
enter as many as you like. If you have multiple datasets (i.e.,
MIR+MAD) then group them using the "group" keyword.
data= None Datafile for this derivative
labels= None Specification string for data labels for deriv. Only
necessary if the wizard does not automatically choose the
correct set of data from your file To find out what the
appropriate strings are, type "phenix.autosol
display_labels=datafile.mtz "
atom_type= None Heavy-atom type for deriv .
sites= None Number of heavy-atom sites for deriv .
sites_file= None PDB or plain-text file with heavy-atom sites. The sites
will be taken from this file if supplied
res_hyss= None resolution for running HYSS for this wavelength/deriv
res_eval= None resolution for evaluation of solutions for this
wavelength/deriv
inano= noinano *inano anoonly Use anomalous differences for deriv .
noinano means do not use anomalous differences. inano means use
anomalous differences and isomorphous differences. anoonly means
use anomalous differences and not iso differences.
f_prime= None F-prime value for this derivative.
f_double_prime= None F-double_prime value for this derivative.
lambda= None wavelength (A). Used with atom_type to calculate f_prime
and f_double_prime if they are not supplied
group= 1 Phasing group(s) this derivative is associated with (Relevant
in cases where you have more than one group of native+derivs or
you have MIR + MAD or SAD)
added_deriv= False Used internally to flag if this derivative was added
automatically
ignore= False Ignore this deriv data
decision_making
always_include_peak= True Choose True to add PEAK dataset on for HYSS if
not automatically chosen
add_extra_if_fa= True Choose True to try an extra file for HYSS if FA
values are used. This may be useful to solve cases
where FA values are poor but their sigmas are small. If
True then the anomalous differences will be used for
HYSS as well.
create_scoring_table= None Choose whether you want a scoring table for
solutions A scoring table is slower but better
desired_coverage= None Choose what probability you want to have that the
correct solution is in your current list of top
solutions. A good value is 0.80. If you set a low
value (0.01) then only one solution will be kept at
any time; if you set a high value, then many solutions
will be kept (and it will take longer).
self_diff_fourier= True Choose whether, in cases where there are
multiple derivatives or multiple datasets, you want
to use difference Fourier analysis on the same
derivative(s) used in phasing (True), or instead
(False) only phasing other derivatives
combine_siblings= True You can specify that in MIR or multiple-dataset
solutions the solutions to combine must all be
ultimately derived by difference fourier from the same
parent. Compare with combine_same_parent_only where
any solutions must have the same immediate parent
(unless one is a composite solution).
max_cc_extra_unique_solutions= 0.5 Specify the maximum value of CC
between experimental maps for two
solutions to consider them substantially
different. Solutions that are within the
range for consideration based on
desired_coverage, but are outside of the
number of allowed max_choices, will be
considered, up to
max_extra_unique_solutions, if they have
a correlation of no more than
max_cc_extra_unique_solutions with all
other solutions to be tested.
max_choices= None Number of choices for solutions to consider. Set
automatically with quick: 1 and thorough:3
max_composite_choices= 8 Number of choices for composite solutions to
consider
max_extra_unique_solutions= None Specify the maximum number of solutions
to consider based on their uniqueness as
well as their high scores. Solutions that
are within the range for consideration based
on desired_coverage, but are outside of the
number of allowed max_choices, will be
considered, up to
max_extra_unique_solutions, if they have a
correlation of no more than
max_cc_extra_unique_solutions with all other
solutions to be tested. Set automatically
with quick:0 ; thorough:2
max_range_to_keep= 4 The range of solutions to be kept is range_to_keep
* SD of the group of solutions. This sets the maximum
of range_to_keep
min_fom= 0.05 Minimum fom of a solution to keep it at all
low_fom= 0.20 If best FOM is less than low_fom, double range_to_keep
minimum_merge_cc= 0.25 Minimum ratio of CC of solutions to expected in
merge_mir keep at all
min_fom_for_dm= 0 Minimum fom of a solution to density modify (otherwise
just copy over phases). This is useful in cases where
the phasing is so weak that density modification does
nothing or makes the phases worse.
min_phased_each_deriv= 1 You can require that the wizard phase at least
this number of solutions from each derivative,
even if they are poor solutions. Usually at least
1 is a good idea so that one derivative does not
dominate the solutions.
n_random= 6 Number of random solutions to generate when setting up
scoring table
res_eval= 0 Resolution for running resolve evaluation (usually 2.5 A) It
will be set automatically if you do not set it
score_individual_offset_list= None Offsets for individual scores in
CC-scoring. Each score will be multiplied
by the score_individual_scale_list value,
then score_individual_offset_list value is
added, to estimate the CC**2 value using
this score by itself. The uncertainty in
the CC**2 value is given by
score_individual_sd_list. NOTE: These
scores are not used in calculation of the
overall score. They are for information
only
score_individual_scale_list= None Scale factors for individual scores in
CC-scoring. Each score will be multiplied
by the score_individual_scale_list value,
then score_individual_offset_list value is
added, to estimate the CC**2 value using
this score by itself. The uncertainty in
the CC**2 value is given by
score_individual_sd_list. NOTE: These
scores are not used in calculation of the
overall score. They are for information
only
score_individual_sd_list= None Uncertainties for individual scores in
CC-scoring. Each score will be multiplied by
the score_individual_scale_list value, then
score_individual_offset_list value is added,
to estimate the CC**2 value using this score
by itself. The uncertainty in the CC**2 value
is given by score_individual_sd_list. NOTE:
These scores are not used in calculation of
the overall score. They are for information
only
score_overall_offset= None Overall offset for scores in CC-scoring. The
weighted scores will be summed, then all
multiplied by score_overall_scale, then
score_overall_offset will be added.
score_overall_scale= None Overall scale factor for scores in CC-scoring.
The weighted scores will be summed, then all
multiplied by score_overall_scale, then
score_overall_offset will be added.
score_overall_sd= None Overall SD of CC**2 estimate for scores in
CC-scoring. The weighted scores will be summed, then
all multiplied by score_overall_scale, then
score_overall_offset will be added. This is an
estimate of CC**2, with uncertainty about
score_overall_sd. Then the square root is taken to
estimate CC and SD(CC), where SD(CC) now depends on CC
due to the square root.
score_type_list= SKEW CORR_RMS You can choose what scoring methods to
include in scoring of solutions in AutoSol. (The
choices available are: CC_DENMOD RFACTOR SKEW
NCS_COPIES NCS_IN_GROUP TRUNCATE FLATNESS CORR_RMS
REGIONS CONTRAST FOM ) NOTE: If you are using Z-SCORE
or BAYES-CC scoring, The default is CC_RMS RFACTOR SKEW
FOM (and NCS_OVERLAP if ncs_copies is at least equal to
ncs_copies_min_for_overlap.
score_weight_list= None Weights on scores for CC-scoring. Enter the
weight on each score in score_type_list. The weighted
scores will be summed, then all multiplied by
score_overall_scale, then score_overall_offset will
be added.
skip_score_list= None You can evaluate some scores but not use them.
Include the ones you do not want to use in the final
score in skip_score_list.
ncs_copies_min_for_overlap= 2 Minimum number of ncs copies (set
automatically from composition and cell or
with ncs_copies=xx) to use NCS_OVERLAP in
scoring
rho_overlap_min= 0.3 Sets minimum average overlap of NCS-related density
to keep NCS. Cutoff of overlap will be rho_overlap_min
for 2 ncs copies, and proportionally smaller
(rho_overlap_min*2/N) for N ncs copies.
rho_overlap_min_scoring= 0.5 Once NCS is found, rho_overlap_min_scoring
sets threshold for whether the NCS is used in
scoring. Cutoff of overlap will be
rho_overlap_min_scoring for 2 ncs copies, and
proportionally smaller
(rho_overlap_min_scoring*2/N) for N ncs copies.
(Compare with rho_overlap_min, which sets
cutoff for finding NCS, not scoring with it)
hyss_scoring
ha_iteration= None Choose whether you want to iterate the heavy-atom
search. With iteration, sites are found with HYSS, then
used to phase and carry out quick density-modification,
then difference Fourier is used to find sites again and
improve their accuracy. Default is to not use
ha_iteration except in multi-dataset or MIR analyses
max_ha_iterations= None Number of iterations of difference Fouriers
in searching for heavy-atom sites. Default is to
set this based on data_quality. Iteration is not
used by default if quick is True.
minimum_improvement= 0 Minimum improvement in score to continue ha
iteration
build_scoring
overall_score_method= *BAYES-CC Z-SCORE You have 2 choices for an
overall scoring method: (1) Sum of individual
Z-scores (Z-SCORE) (2) Bayesian estimate of CC
of map to perfect model (BAYES-CC) You can
specify which scoring criteria to include with
score_type_list (default is SKEW CORR_RMS for
BAYES-CC and CC RFACTOR SKEW FOM for Z-SCORE.
Additionally, if NCS is present, NCS_OVERLAP is
used by default in the Z-SCORE method).
r_switch= 0.4 R-value criteria for deciding whether to use R-value or
residues built. A good value is 0.40
acceptable_quality= 40 You can specify the minimum overall quality of
a model (as defined by overall_score_method) to
be considered acceptable
acceptable_secondary_structure_cc= 0.35 You can specify the minimum
correlation of density from a
secondary structure model to be
considered acceptable
trace_chain= True You can build a CA-only model right after density
modification using trace_chain
trace_chain_score= False You can score density-modified maps with the
number of residues built with regular
secondary-structure using trace_chain.
dev_scoring
random_scoring= False For testing purposes you can generate random
scores
use_perfect= False You can use the CC between each solution and
hklperfect in scoring. This is only for methods
development purposes.
hklperfect= None You can supply an mtz file with idealized
coefficients for a map. This will be compared with all
maps calculated during structure solution
perfect_labels= None Labels for input data columns for hklperfect if
present. Typical value: "FP PHIC FOM"
scaling
remove_aniso= Auto *True False Choose if you want to apply a correction
for anisotropy to the data. True means always apply
correction, No means never apply it, Auto means apply it
if the data is severely anisotropic (recommended=True). If
you set remove_aniso=Auto then if the range of anisotropic
B-factors is greater than delta_b_for_auto_remove_aniso
and the ratio of the largest to the smallest less than
ratio_b_for_auto_remove_aniso then the correction will be
applied. Anisotropy correction will be applied to all
input data before scaling. If used, the default overall
target B factor is is minimum of (max_b_iso, lowest B of
datasets, target_b_ratio*resolution)
b_iso= None Target overall B value for anisotropy correction. Ignored if
remove_aniso = False. If None, default is minimum of (max_b_iso,
lowest B of datasets, target_b_ratio*resolution)
max_b_iso= 40. Default maximum overall B value for anisotropy
correction. Ignored if remove_aniso = False. Ignored if b_iso
is set. If used, default is minimum of (max_b_iso, lowest B
of datasets, target_b_ratio*resolution)
target_b_ratio= 10. Default ratio of target B value to resolution for
anisotropy correction. Ignored if remove_aniso = False.
Ignored if b_iso is set. If used, default is minimum of
(max_b_iso, lowest B of datasets,
target_b_ratio*resolution)
localscale_before_phaser= True You can apply SOLVE localscaling to SAD
data before passing it to Phaser for SAD
phasing
delta_b_for_auto_remove_aniso= 20 Choose what range of aniso B values is
so big that you want to correct for
anisotropy by default. Both ratio_b and
delta_b must be large to correct. See
also ratio_b_for_auto_remove_aniso. See
also "remove_aniso" which
overrides this default if set to
"True"
ratio_b_for_auto_remove_aniso= 1.0 Choose what ratio aniso B values is
so big that you want to correct for
anisotropy by default. Both ratio_b and
delta_b must be large to correct. see
also delta_b_for_auto_remove_aniso See
also "remove_aniso" which
overrides this default if set to
"True"
test_remove_aniso= True Choose whether you want to try applying or not
applying an anisotropy correction if the run fails.
First your original selection for applying or not
will be tried, and then the opposite will be tried if
the run fails.
use_sca_as_is= True Choose True to allow use of sca files (and mtz
files) without conversion even if the space group is
changed. If False, then original index files will always
be converted to premerged if the space group is changed
heavy_atom_search
min_hyss_cc= 0.05 Minimum CC of a heavy-atom solution in HYSS to keep it
at all
acceptable_cc_hyss= 0.2 Solutions with CC better than acceptable_cc_hyss
will not be rescored.
good_cc_hyss= 0.3 Hyss will be run up to best_of_n_hyss_always times at
a given resolution. If the best CC value is greater than
good_cc_hyss and the number of sites found is at least
min_fraction_of_sites_found times the number expected and
Hyss was tried at least best_of_n_hyss times, then the
search is ended. Also if thoroughness=quick and a solution
with CC at least as high as good_cc_hyss is found, no more
searches will be done at all
n_add_res_max= 2 Hyss will be run at up to n_add_res_max+1 resolutions
starting with res_hyss and adding increments of
add_res_max/n_add_res_max. If the best CC value is
greater than good_cc_hyss then no more resolutions are
tried.
add_res_max= 2 Hyss will be run at up to n_add_res_max+1 resolutions
starting with res_hyss and adding increments of
add_res_max/n_add_res_max. If the best CC value is greater
than good_cc_hyss then no more resolutions are tried.
try_recommended_resolution_for_hyss= True If yes, then hyss will be run
at recommended_resolution based on
anomalous signal in addition to
default resolution if CC at default
resolution is less than
good_cc_hyss and
recommended_resolution is more than
0.1 A less than default
hyss_runs_min= 2 If there are multiple derivatives or candidate
wavelengths for HYSS, run at least hyss_runs_min of
these.
best_of_n_hyss= 1 Hyss will be run up to best_of_n_hyss_always times at
a given resolution. If the best CC value is greater than
good_cc_hyss and the number of sites found is at least
min_fraction_of_sites_found times the number expected
and Hyss was tried at least best_of_n_hyss times, then
the search is ended if hyss_runs_min data files have
been attempted.
best_of_n_hyss_always= 10 Hyss will be run up to best_of_n_hyss_always
times at a given resolution. If the best CC value
is greater than good_cc_hyss and the number of
sites found is at least
min_fraction_of_sites_found times the number
expected and Hyss was tried at least
best_of_n_hyss times, then the search is ended if
hyss_runs_min data files have been attempted.
min_fraction_of_sites_found= 0.667 Hyss will be run up to
best_of_n_hyss_always times at a given
resolution. If the best CC value is greater
than good_cc_hyss and the number of sites
found is at least
min_fraction_of_sites_found times the
number expected and Hyss was tried at least
best_of_n_hyss times, then the search is
ended if hyss_runs_min data files have been
attempted.
max_single_sites= 5 In sites_from_denmod a core set of sites that are
strong is identified. If the hand of the solution is
known then additional sites are added all at once up
to the expected number of sites. Otherwise sites are
added one at a time, up to a maximum number of tries
of max_single_sites
hyss_enable_early_termination= True You can specify whether to stop HYSS
as soon as it finds a convincing solution
(True, default) or to keep trying...
hyss_general_positions_only= True Select True if you want HYSS only to
consider general positions and ignore sites
on special positions. This is appropriate
for SeMet or S-Met solutions, not so
appropriate for heavy-atom soaks
hyss_min_distance= 3.5 Enter the minimum distance between heavy-atom
sites to keep them in HYSS
hyss_n_fragments= 3 Enter the number of fragments in HYSS
hyss_n_patterson_vectors= 33 Enter the number of Patterson vectors to
consider in HYSS
hyss_random_seed= 792341 Enter an integer as random seed for HYSS
res_hyss= None Overall resolution for running HYSS (usually default is
fine)
use_measurability= True Use measurability (from xtriage) to estimate
recommended resolution for HYSS and for initial
phasing. Only applies to MAD/SAD phasing. Alternative
is to use signal-to-noise from Solve scaling.
use_phaser_rescoring= False Run phaser rescoring for HYSS heavy-atom
search (only SAD data) if initial try fails
mad_ha_n= None Normally not used. Use instead "sites" for a
wavelength. Number of anomalously-scattering atoms in the au
mad_ha_type= "Se" Normally not used. Use instead "atom_type"
for a wavelength. Anomalously-scattering or heavy atom
type. For" example, Se or Au. NOTE: if you want Phaser to
add additional heavy-atoms of other types, you can specify
them with mad_ha_add_list.
phasing
do_madbst= True Choose whether you want to carry out FA calculation
Skipping it speeds up MAD phasing but may reduce the ability
to find the sites with HYSS
overallscale= False You can choose to have only an overall scale factor
for this dataset (no local scaling applied). Use this if
your data is already fully scaled.
res_phase= 0 Enter the high-resolution limit for phasing (0= use all)
phase_full_resolution= True You can choose to use the full resolution of
the data in phasing, instead of using the
recommended_resolution. This is always a good
idea with Phaser phases.
fixscattfactors= None For SOLVE phasing and MAD data you can choose
whether scattering factors are to be fixed by choosing
True to fix them or False to refine them. Normally
choose True (fix) if the data are weak and False
(refine) if the data are strong.
fixscattfactors_in_phasing= False Fix scattering factors in phasing
step. For SOLVE phasing and MAD data you can
choose whether scattering factors are to be
fixed by choosing True to fix them or False
to refine them. Normally False. This command
only applies to the phasing step and not
initial heavy-atom refinement. It does not
apply to Phaser SAD phasing.
fix_xyz_in_phasing= None Fix coordinates in phasing step. For SOLVE
phasing and MAD data you can choose whether ha
coordinates are to be fixed by choosing True to fix
them or False to refine them. May be useful in
maintaining the coordinates of the solutions that
were tested in initial phasing steps. If None, then
it will be set to True if the resolution of final
phasing step is higher than the highest resolution
of test phasing runs This command only applies to
the phasing step and not initial heavy-atom
refinement. It does not apply to Phaser SAD phasing
have_hand= False Normally you will not know the hand of the heavy-atom
substructure, so have_hand=False. However if you do know it
(you got the sites from a difference Fourier or you know the
answer another way) you can specify that the hand is known.
id_scale_ref= None By default the datafile with the highest resolution
is used for the first step in scaling of MAD data. You can
choose to use any of the datafiles in your MAD dataset.
NOTE: not applicable for multi-dataset analyses
ratio_out= 10. You can choose the ratio of del ano or del iso to the rms
in the shell for rejection of a reflection. Default = 10.
ratmin= 0. Reflections with I/sigI less than ratmin will be ignored when
read in.
require_nat= True Choose yes to skip any reflection with no native (for
SIR) or no data (MAD/SAD) or where anom difference is very
large. This keyword (default=True) allows the routines in
SOLVE to remove reflections with an implausibly large
anomalous difference (greater than ratio_out times the rms
anomalous difference).
ikeepflag= 1 You can choose to keep all reflections in merging steps.
This is separate from rejecting reflections with high iso or
ano diffs. Default=1 (keep them)
phasing_method= SOLVE *PHASER You can choose to phase with SOLVE or with
Phaser. (Only applies to SAD phasing at present)
input_partpdb_file= None You can enter a PDB file (usually from
molecular replacement) for use in identifying
heavy-atom sites and phasing. NOTE 1: This procedure
works best if the model is refined. NOTE 2: This
file is only used in SAD phasing with Phaser on a
single dataset. In all other cases it is ignored.
NOTE 3: The output phases in phaser_xx.mtz will
contain both SAD and model information. They are not
completely suitable for use with AutoBuild or other
iterative model-building procedures because the
phases are not entirely experimental (but they may
work).
partpdb_rms= 1
phaser_completion= True You can choose to use phaser log-likelihood
gradients to complete your heavy-atom sites. This can
be used with or without the ha_iteration option.
use_phaser_hklstart= True You can choose to start density modification
with FWT PHWT from Phaser (Only applies to SAD
phasing at present)
combine_same_parent_only= False You can choose to only combine solutions
with the same parent (and that have a parent)
in MIR, unless one solution is a composite.
Compare with combine_siblings in which case
the solutions do not have to have the same
immediate parents, but can be derived from the
same ultimate parent through several
difference fourier steps.
skip_extra_phasing= Auto True *False You can choose to skip an extra
phasing step to speed up the process. If the extra
step is used then the evaluation of solutions is
done with data to res_eval (2.5 A) and then all the
data are used in an extra phasing step.
read_sites= False Choose if you want to enter ha sites from a file The
name of the file will be requested after scaling is
finished. The file can have sites in fractional coordinates
or be a PDB file. Normally you do not need to set this. Set
automatically if you specify a sites_file
f_double_prime_list= None f-double-prime for the heavy-atom for this
dataset Normally not used. Use f_double_prime for
wavelength or deriv
f_prime_list= None f-prime for the heavy-atom for this dataset Normally
not used. Use f_prime for wavelength or deriv
mad_ha_add_f_double_prime_list= None F-double_prime values of additional
heavy-atom types. You must specify the
same number of entries of
mad_ha_add_f_double_prime_list as you do
for mad_ha_add_f_prime_list and for
mad_ha_add_list. Only use for Phaser SAD
phasing with a single dataset
mad_ha_add_f_prime_list= None F-prime values of additional heavy-atom
types. You must specify the same number of
entries of mad_ha_add_f_prime_list as you do
for mad_ha_add_f_double_prime_list and for
mad_ha_add_list. Only use for Phaser SAD
phasing with a single dataset
mad_ha_add_list= None You can specify heavy atom types in addition to
the one you named in mad_ha_type. The heavy-atoms found
in initial HySS searches will be given the type of
mad_ha_type, and Phaser (if used for phasing) will try
to find additional heavy atoms of both the type
mad_ha_type and any listed in mad_ha_add_list. You must
also specify the same number of mad_ha_add_f_prime_list
entries and of mad_ha_add_f_double_prime_list entries.
Only use for Phaser SAD phasing with a single dataset
n_ha_list= None Enter a guess of number of HA sites Normally not used.
Use sites in deriv instead
nat_der_list= None Enter Native or a heavy-atom symbol (Pt, Se) Normally
not used. Use atom_type in deriv instead
density_modification
fix_xyz= False You can choose to not refine coordinates, and instead to
fix them to the values found by the heavy-atom search.
fix_xyz_after_denmod= None When sites are found after density
modification you can choose whether you want to
fix the coordinates to the values found in that
map.
hl_in_resolve= False AutoSol normally does not write out HL coefficients
in the resolve.mtz file with density-modified phases. You
can turn them on with hl_in_resolve=True
mask_type= *histograms probability wang classic Choose method for
obtaining probability that a point is in the protein vs
solvent region. Default is "histograms". If you
have a SAD dataset with a heavy atom such as Pt or Au then
you may wish to choose "wang" because the histogram
method is sensitive to very high peaks. Options are:
histograms: compare local rms of map and local skew of map to
values from a model map and estimate probabilities. This one
is usually the best. probability: compare local rms of map to
distribution for all points in this map and estimate
probabilities. In a few cases this one is much better than
histograms. wang: take points with highest local rms and
define as protein. Classic runs classical density
modification with solvent flipping.
test_mask_type= None You can choose to have AutoSol test histograms/wang
methods for identifying solvent region and statistical
vs classical density modification based on the final
density modification r-factor.
mask_cycles= 5 Number of mask cycles in density modification (5 is usual
for thorough density modification
minor_cycles= 10 Number of minor cycles in density modification for each
mask cycle (10 is usual for thorough density modification)
thorough_denmod= None Choose whether you want to go for density
modification (usual) or quick (speeds it up and for a
terrible map is sometimes better)
truncate_ha_sites_in_resolve= Auto *True False You can choose to
truncate the density near heavy-atom sites
at a maximum of 2.5 sigma. This is useful
in cases where the heavy-atom sites are
very strong, and rarely hurts in cases
where they are not. The heavy-atom sites
are specified with
"input_ha_file" and radius is
rad_mask
rad_mask= None You can define the radius for calculation of the protein
mask Applies only to truncate_ha_sites_in_resolve. Default is
resolution of data.
use_ncs_in_denmod= True This script normally uses available ncs
information in density modification. Say No to skip
this. See also find_ncs
mask_as_mtz= False Defines how omit_output_mask_file
ncs_output_mask_file and protein_output_mask_file are
written out. If mask_as_mtz=False it will be a ccp4 map. If
mask_as_mtz=True it will be an mtz file with map
coefficients FP PHIM FOMM (all three required)
protein_output_mask_file= None Name of map to be written out
representing your protein (non-solvent)
region. If mask_as_mtz=False the map will be a
ccp4 map. If mask_as_mtz=True it will be an
mtz file with map coefficients FP PHIM FOMM
(all three required)
ncs_output_mask_file= None Name of map to be written out representing
your ncs asymmetric unit. If mask_as_mtz=False the
map will be a ccp4 map. If mask_as_mtz=True it
will be an mtz file with map coefficients FP PHIM
FOMM (all three required)
omit_output_mask_file= None Name of map to be written out representing
your omit region. If mask_as_mtz=False the map
will be a ccp4 map. If mask_as_mtz=True it will
be an mtz file with map coefficients FP PHIM FOMM
(all three required)
use_hl_anom_in_denmod= None Default is False (use HL coefficients in
density modification) Allows you to specify that
HL coefficients including only the phase
information from the imaginary (anomalous
difference) contribution from the anomalous
scatterers are to be used in density
modification. Two sets of HL coefficients are
produced by Phaser. HLA HLB etc are HL
coefficients including the contribution of both
the real scattering and the anomalous
differences. HLanomA HLanomB etc are HL
coefficients including the contribution of the
anomalous differences alone. These HL
coefficients for anomalous differences alone are
the ones that you will want to use in cases where
you are bringing in model information that
includes the real scattering from the model used
in Phaser, such as when you are carrying out
density modification with a model or refinement
of a model If use_hl_anom_in_denmod=True then the
HLanom HL coefficients from Phaser are used in
density modification
use_hl_anom_in_denmod_with_model= None Default is True if
input_partpdb_file is included. (See
also use_hl_anom_in_denmod) If
use_hl_anom_in_denmod=True then the
HLanom HL coefficients from Phaser are
used in density modification with a
model
model_building
build= True Build model after density modification?
phase_improve_and_build= True Carry out cycles of phase improvement with
quick model-building followed by a full
model-building step NOTE: This is now the
standard model-building approach for AutoSol
build_type= *RESOLVE RESOLVE_AND_BUCCANEER You can choose to build
models with RESOLVE or with RESOLVE and BUCCANEER #and
TEXTAL and how many different models to build with RESOLVE.
The more you build, the more likely to get a complete model.
Note that rebuild_in_place can only be carried out with
RESOLVE model-building. For BUCCANEER model building you
need CCP4 version 6.1.2 or higher and BUCCANEER version
1.3.0 or higher
resolve Parameters specific for RESOLVE model-building
n_cycle_build= None Choose number of cycles (3).
refine= True This script normally refines the model during building.
Say False to skip refinement
ncycle_refine= 3 Choose number of refinement cycles (3)
number_of_builds= None Number of different solutions to build models
for
number_of_models= None This parameter lets you choose how many
initial models to build with RESOLVE within a
single build cycle.
resolution_build= 0 Enter the high-resolution limit for
model-building. If 0.0, the value of resolution is
used as a default.
helices_strands_only= False You can choose to use a quick
model-building method that only builds
secondary structure. At low resolution this may
be both quicker and more accurate than trying
to build the entire structure If you are
running the AutoSol Wizard, normally you should
choose 'False' as standard building is quick.
When your structure is solved by AutoSol, go on
to AutoBuild and build a more complete model
(still using helices_strands_only=False). NOTE:
helices_strands_only does not apply in AutoSol
if phase_improve_and_build=True
helices_strands_start= False You can choose to use a quick
model-building method that builds secondary
structure as a way to get started...then model
completion is done as usual. (Contrast with
helices_strands_only which only does secondary
structure)
cc_helix_min= None Minimum CC of helical density to map at low
resolution when using helices_strands_only
cc_strand_min= None Minimum CC of strand density to map when using
helices_strands_only
trace_loops= False Use trace_loops algorithm in loop fitting
standard_loops= True Use standard_loops algorithm in loop fitting
loop_lib= False Use loop_lib algorithm in loop fitting
fit_loops= True You can fit loops automatically if sequence alignment
has been done.
loop_cc_min= 0.4 You can specify the minimum correlation of density
from a loop with the map.
group_ca_length= 4 In resolve building you can specify how short a
fragment to keep. Normally 4 or 5 residues should be
the minimum.
group_length= 2 In resolve building you can specify how many
fragments must be joined to make a connected group that
is kept. Normally 2 fragments should be the minimum.
input_compare_file= None If you are rebuilding a model or already
think you know what the model should be, you can
include a comparison file in rebuilding. The
model is not used for anything except to write
out information on coordinate differences in the
output log files. NOTE: this feature does not
always work correctly.
n_random_frag= 0 In resolve building you can randomize each fragment
slightly so as to generate more possibilities for
tracing based on extending it.
n_random_loop= 3 Number of randomized tries from each end for
building loops If 0, then one try. If N, then N
additional tries with randomization based on
rms_random_loop.
offsets_list= 53 7 23 You can specify an offset for the orientation
of the helix and strand templates in building. This is
used in generating different starting models.
remove_outlier_segments_z_cut= 3.0 You can remove any segments that
are not assigned to sequence during
model-building if the mean density at
atomic positions are more than
remove_outlier_segments_z_cut sd lower
than the mean for the structure.
resolve_command_list= None Commands for resolve. One per line in the
form: keyword value value can be optional
Examples: coarse_grid resolution 200 2.0 hklin
test.mtz NOTE: for command-line usage you need
to enclose the whole set of commands in double
quotes (") and each individual command in
single quotes (') like this:
resolve_command_list="'no_build'
'b_overall 23' "
solve_command_list= None Commands for solve. One per line in the
form: keyword value, where value can be optional
Examples: verbose resolution 200 2.0 For
specification from command_line enclose each
command and value in quotes, and then use a
different type of quotes to enclose all of them
(same as resolve_command_list)
rms_random_frag= None Rms random position change added to residues on
ends of fragments when extending them If you enter a
negative number, defaults will be used.
rms_random_loop= None Rms random position change added to residues on
ends of loops in tries for building loops If you
enter a negative number, defaults will be used.
semet= None You can specify that the dataset that is used for
refinement is a selenomethionine dataset, and that the model
should be the SeMet version of the protein, with all SD of MET
replaced with Se of MSE. By default if your heavy-atom is Se
then this will be set to True
use_met_in_align= Auto *True False You can use the heavy-atom
positions in input_ha_file as markers for Met SD
positions.
start_chains_list= None You can specify the starting residue number
for each of the unique chains in your structure.
If you use a sequence file then the unique chains
are extracted and the order must match the order
of your starting residue numbers. For example, if
your sequence file has chains A and B (identical)
and chains C and D (identical to each other, but
different than A and B) then you can enter 2
numbers, the starting residues for chains A and C.
NOTE: you need to specify an input sequence file
for start_chains_list to be applied.
thorough_loop_fit= None Try many conformations and accept them even
if the fit is not perfect. If you say True the
parameters for thorough loop fitting are:
n_random_loop=100 rms_random_loop=0.3
rho_min_main=0.5 while if you say No those for
quick loop fitting are: n_random_loop=20
rms_random_loop=0.3 rho_min_main=1.0
trace_as_lig= False You can specify that in building steps the ends
of chains are to be extended using the LigandFit
algorithm. This is default for nucleic acid
model-building.
use_any_side= False You can choose to have resolve model-building
place the best-fitting side chain at each position,
even if the sequence is not matched to the map.
ncs
find_ncs= Auto *True False The wizard normally deduces ncs information
from the NCS in heavy atom sites, and then later from any NCS
in chains of models that are built during model-building. The
update is done each cycle in which an improved model is
obtained. Say No to skip this update.
ncs_copies= None Number of copies of the molecule in the au (note: only
one type of molecule allowed at present)
ncs_refine_coord_sigma_from_rmsd= False You can choose to use the
current NCS rmsd as the value of the
sigma for NCS restraints. See also
ncs_refine_coord_sigma_from_rmsd_ratio
ncs_refine_coord_sigma_from_rmsd_ratio= 1 You can choose to multiply the
current NCS rmsd by this value
before using it as the sigma for
NCS restraints See also
ncs_refine_coord_sigma_from_rmsd
optimize_ncs= True This script normally deduces ncs information from the
NCS in chains of models that are built during iterative
model-building. Optimize NCS adds a step to try and make
the molecule formed by NCS as compact as possible, without
losing any point-group symmetry.
refine_with_ncs= True This script can allow phenix.refine to
automatically identify NCS and use it in refinement.
refinement
refine_b= True You can choose whether phenix.refine is to refine
individual atomic displacement parameters (B values)
refine_se_occ= True You can choose to refine the occupancy of SE atoms
in a SEMET structure (default=True). This only applies if
semet=true
skip_clash_guard= True Skip refinement check for atoms that clash
correct_special_position_tolerance= None Adjust tolerance for special
position check. If 0., then check
for clashes near special positions
is not carried out. This sometimes
allows phenix.refine to continue
even if an atom is near a special
position. If 1., then checks within
1 A of special positions. If None,
then uses phenix.refine default. (1)
use_mlhl= True This script normally uses information from the input file
(HLA HLB HLC HLD) in refinement. Say No to only refine on Fobs
place_waters= True You can choose whether phenix.refine automatically
places ordered solvent (waters) during the refinement
process.
refinement_resolution= 0 Enter the high-resolution limit for refinement
only. This high-resolution limit can be different
than the high-resolution limit for other steps.
The default ("None" or 0.0) is to use
the overall high-resolution limit for this run
(as set by resolution)
ordered_solvent_low_resolution= None You can choose what resolution
cutoff to use fo placing ordered solvent
in phenix.refine. If the resolution of
refinement is greater than this cutoff,
then no ordered solvent will be placed,
even if
refinement.main.ordered_solvent=True.
link_distance_cutoff= 3 You can specify the maximum bond distance for
linking residues in phenix.refine called from the
wizards.
r_free_flags_fraction= 0.1 Maximum fraction of reflections in the free R
set. You can choose the maximum fraction of
reflections in the free R set and the maximum
number of reflections in the free R set. The
number of reflections in the free R set will be
up the lower of the values defined by these two
parameters.
r_free_flags_max_free= 2000 Maximum number of reflections in the free R
set. You can choose the maximum fraction of
reflections in the free R set and the maximum
number of reflections in the free R set. The
number of reflections in the free R set will be
up the lower of the values defined by these two
parameters.
r_free_flags_use_lattice_symmetry= True When generating r_free_flags you
can decide whether to include lattice
symmetry (good in general, necessary
if there is twinning).
r_free_flags_lattice_symmetry_max_delta= 5 You can set the maximum
deviation of distances in the
lattice that are to be
considered the same for
purposes of generating a
lattice-symmetry-unique set of
free R flags.
allow_overlapping= False You can allow atoms in your ligand files to
overlap atoms in your protein/nucleic acid model.
This overrides 'keep_pdb_atoms' Useful in early
stages of model-building and refinement The ligand
atoms get the altloc indicator 'L' NOTE: The ligand
occupancy will be refined by default if you set
allow_overlapping=True (because of the altloc
indicator) You can turn this off with
fix_ligand_occupancy=True
fix_ligand_occupancy= None If allow_overlapping=True then ligand
occupancies are refined as a group. You can turn
this off with fix_ligand_occupancy=true NOTE: has
no effect if allow_overlapping=False
remove_outlier_segments= True You can remove any segments that are not
assigned to sequence if their mean B values are
more than remove_outlier_segments_z_cut sd
higher than the mean for the structure. NOTE:
this is done after refinement, so the R/Rfree
are no longer applicable; the remarks in the
PDB file are removed
twin_law= None You can specify a twin law for refinement like this:
twin_law='-h,k,-l'
use_hl_anom_in_refinement= None Default is True if input_partpdb_file is
used (See also use_hl_anom_in_denmod). If
use_hl_anom_in_refinement=True then the
HLanom HL coefficients from Phaser are used
in refinement
include_ha_in_refinement= None You can choose to include your heavy-atom
sites in the model for refinement. This is a
good idea if your structure includes these
heavy-atom sites (i.e., for SAD or MAD
structures where you are not using a native
dataset). Heavy-atom sites that overlap an
atom in your model will be ignored. Default is
True unless the dataset is SAD/MAD with Se or
S
display
number_of_solutions_to_display= 1 Number of solutions to put on screen
and to write out
solution_to_display= 0 Solution number of the solution to display and
write out ( use 0 to let the wizard display the top
solution)
general
data_quality= *moderate strong weak The defaults are set for you
depending on the anticipated data quality. You can choose
"moderate" if you are unsure.
thoroughness= *quick thorough You can try to run quickly and see if you
can get a solution ("quick") or more thoroughly
to get the best possible solution ("thorough").
nproc= 1 You can specify the number of processors to use (nproc) and the
number of batches to divide the data into for parallel jobs.
Normally you will set nproc to the number of processors available
and leave nbatch alone. If you leave nbatch as None it will be
set automatically, with a value depending on the Wizard. This is
recommended. The value of nbatch can affect the results that you
get, as the jobs are not split into exact replicates, but are
rather run with different random numbers. If you want to get the
same results, keep the same value of nbatch.
nbatch= 1 You can specify the number of processors to use (nproc) and
the number of batches to divide the data into for parallel jobs.
Normally you will set nproc to the number of processors
available and leave nbatch alone. If you leave nbatch as None it
will be set automatically, with a value depending on the Wizard.
This is recommended. The value of nbatch can affect the results
that you get, as the jobs are not split into exact replicates,
but are rather run with different random numbers. If you want to
get the same results, keep the same value of nbatch.
keep_files= overall_best* phaser_*.mtz resolve_*.mtz solve_*.mtz
ha_*.pdb List of files that are not to be cleaned up.
wildcards permitted
coot_name= "coot" If your version of coot is called something else, then
you can specify that here.
i_ran_seed= 72432 Random seed (positive integer) for model-building and
simulated annealing refinement
raise_sorry= False You can have any failure end with a Sorry instead of
simply printout to the screen
background= True When you specify nproc=nn, you can run the jobs in
background (default if nproc is greater than 1) or
foreground (default if nproc=1). If you set run_command=qsub
(or otherwise submit to a batch queue), then you should set
background=False, so that the batch queue can keep track of
your runs. There is no need to use background=True in this
case because all the runs go as controlled by your batch
system. If you use run_command='sh ' (or similar, sh is
default) then normally you will use background=True so that
all the jobs run simultaneously.
max_wait_time= 1.0 You can specify the length of time (seconds) to wait
when looking for a file. If you have a cluster where jobs
do not start right away you may need a longer time to
wait. The symptom of too short a wait time is 'File not
found'
wait_between_submit_time= 1.0 You can specify the length of time
(seconds) to wait between each job that is
submitted when running sub-processes. This can
be helpful on NFS-mounted systems when running
with multiple processors to avoid file
conflicts. The symptom of too short a
wait_between_submit_time is File exists:....
cache_resolve_libs= True Use caching of resolve libraries to speed up
resolve
resolve_size= 12 Size for solve/resolve
("","_giant",
"_huge","_extra_huge" or a number
where 12=giant 18=huge
check_run_command= False You can have the wizard check your run command
at startup
run_command= "sh " When you specify nproc=nn, you can run the
subprocesses as jobs in background with sh (default) or
submit them to a queue with the command of your choice
(i.e., qsub ). If you have a multi-processor machine, use
sh. If you have a cluster, use qsub or the equivalent
command for your system. NOTE: If you set run_command=qsub
(or otherwise submit to a batch queue), then you should set
background=False, so that the batch queue can keep track of
your runs. There is no need to use background=True in this
case because all the runs go as controlled by your batch
system. If nproc is greater than 1 and you use
run_command='sh '(or similar, sh is default) then normally
you will use background=True so that all the jobs run
simultaneously.
last_process_is_local= True If true, run the last process in a group in
background with sh as part of the job that is
submitting jobs. This prevents having the job
that is submitting jobs sit and wait for all the
others while doing nothing
skip_r_factor= False You can skip R-factor calculation if refinement is
not done and maps_only=True
skip_xtriage= False You can bypass xtriage if you want. This will
prevent you from applying anisotropy corrections, however.
base_path= None You can specify the base path for files (default is
current working directory)
temp_dir= None Define a temporary directory (it must exist)
clean_up= True At the end of the entire run the TEMP directories will be
removed if clean_up is True. The default is yes, delete these
directories. If you want to remove them after your run is
finished use a command like "phenix.autobuild run=1
clean_up=True" Files listed in keep_files will not be
deleted
solution_output_pickle_file= None At end of run, write solutions to this
file in output directory if defined
title= None Enter any text you like to help identify what you did in
this run
top_output_dir= None This is used in subprocess calls of wizards and to
tell the Wizard where to look for the STOPWIZARD file.
wizard_directory_number= None This is used by the GUI to define the run
number for Wizards. It is the same as
desired_run_number NOTE: this value can only be
specified on the command line, as the directory
number is set before parameters files are read.
verbose= False Command files and other verbose output will be printed
extra_verbose= False Facts and possible commands will be printed every
cycle if True
debug= False You can have the wizard stop with error messages about the
code if you use debug. NOTE: you cannot use Pause with debug.
Additionally the output goes to the terminal if you specify
"debug=True"
require_nonzero= True Require non-zero values in data columns to
consider reading in.
remove_path_word_list= None List of words identifying paths to remove
from PATH These can be used to shorten your PATH.
For example... cns ccp4 coot would remove all
paths containing these words except those also
containing phenix. Capitalization is ignored.
fill= False Fill in all missing reflections to resolution res_fill.
Applies to density modified maps. See also filled_2fofc_maps in
autobuild.
res_fill= None Resolution for filling in missing data (default = highest
resolution of any datafile). Only applies to density modified
maps. Default is fill to high resolution of data. Ignored if
fill=False
run_control
coot= None Set coot to True and optionally run=[run-number] to run Coot
with the current model and map for run run-number. In some wizards
(AutoBuild) you can edit the model and give it back to PHENIX to
use as part of the model-building process. If you just say coot
then the facts for the highest-numbered existing run will be
shown.
ignore_blanks= None ignore_blanks allows you to have a command-line
keyword with a blank value like
"input_lig_file_list="
stop= None You can stop the current wizard with "stopwizard"
or "stop". If you type "phenix.autobuild run=3
stop" then this will stop run 3 of autobuild.
display_facts= None Set display_facts to True and optionally
run=[run-number] to display the facts for run run-number.
If you just say display_facts then the facts for the
highest-numbered existing run will be shown.
display_summary= None Set display_summary to True and optionally
run=[run-number] to show the summary for run
run-number. If you just say display_summary then the
summary for the highest-numbered existing run will be
shown.
carry_on= None Set carry_on to True to carry on with highest-numbered
run from where you left off.
run= None Set run to n to continue with run n where you left off.
copy_run= None Set copy_run to n to copy run n to a new run and continue
where you left off.
display_runs= None List all runs for this wizard.
delete_runs= None List runs to delete: 1 2 3-5 9:12
display_labels= None display_labels=test.mtz will list all the labels
that identify data in test.mtz. You can use the label
strings that are produced in AutoSol to identify which
data to use from a datafile like this:
peak.data="F+ SIGF+ F- SIGF-". The entire
string in quotes counts here You can use the individual
labels from these strings as identifiers for data
columns in AutoSol or AutoBuild like this:
input_refinement_labels="FP SIGFP FreeR_flags"
# each individual label counts
dry_run= False Just read in and check parameter names
params_only= False Just read in and return parameter defaults. Not for
general use
display_all= False Just read in and display parameter defaults
special_keywords
write_run_directory_to_file= None Writes the full name of a run
directory to the specified file. This can
be used as a call-back to tell a script
where the output is going to go.
non_user_parameters These are obsolete parameters and parameters that the
wizards use to communicate among themselves. Not
normally for general use.
gui_output_dir= None Used only by the GUI
allow_negative_f_double_prime= False Allow a negative f-double-prime
value
inano_list= None Choose inano for including anomalous differences and
noinano not to include them and anoonly for just anomalous
differences (no isomorphous differences) Not normally used.
Use inano in deriv instead
ha_sites_file= None Not normally used. Use sites_file for wavelength or
deriv
expt_type= *Auto mad sir sad Not normally used. Determined automatically
from your inputs for wavelength and native/deriv. Experiment
type (MAD SIR SAD) NOTE: Please treat MIR experiments as a
set of SIR experiments. NOTE: The default for this keyword is
Auto which means "carry out normal process to guess this
keyword". If you have a single file, then it is assumed
to be SAD. If you specify native.data and deriv.data it is
SIR, if you specify peak.data and infl.data it is MAD. If the
Wizard does not guess correctly, you can set it with this
keyword.
wavelength_list= None Optional wavelength of x-ray data (A) Not normally
used. Use wavelength/deriv and lambda instead
wavelength_name_list= None Names of wavelengths. Not normally used. Use
wavelength/deriv and name instead
sg= None Obsolete. Use space_group instead
| |||||||||