Analyse results
Output files
For every iteration, RELION will output the following files:
rootname_it000???_class000???.mrc
(orrootname_it000???_class000???.mrcs
for 2D refinements)rootname_it000???_optimiser.star
rootname_it000???_mlmodel.star
rootname_it000???_data.star
These files contain the following information, respectively:
- The images of the refined 2D/3D structures.
- General information about the optimisation process.
- Information about the refined model parameters apart from the images (e.g. the noise spectra, the spherical average of the signal-to-noise ratios in the reconstructed structures, the distribution of the images over the classes, the angular distributions, etc.
- For each of the individual experimental images: information about their CTF, optimal orientation, translation and class assignment, normalisation correction, height of the (normalised) probability distribution, etc .
What to look for
The most common indicators to look out for are given below. For a complete list of all metadata labels, on the command-line type: relion_refine --print_metadata_labels
.
Monitor resolution
The highest resolution for which at least one of the models has SSNR^MAP>1 is stored as _rlnCurrentResolution in the _optimiser.star
files. Therefore, progress in terms of resolution may be monitored using:
grep rlnCurrentResolution *optimiser.star
The fall-off of SSNR^MAP with resolution for each model is stored in the tables called data_mlmodel_class_N
(with N being the number of the corresponding class) in the _mlmodel.star
files. It is often insightful to have a look at these tables in the files themselves. Alternatively, one may use the relion_star_plottable
script to make a plot (requires gnuplot to be installed), using:
relion_star_plottable rootname_it000025_mlmodel.star data_mlmodel_class_1 rlnSsnrMap rlnResolution
Although it may be better to rerun gnuplot and plot the produced plot with a limited Y-range:
gnuplot
gnuplot> set yrange [0:20]
gnuplot> load "gnuplot.plt"
Monitor class distribution
Likewise, the distribution of all images over the various classes is stored in the table called data_mlmodel_classes
in the _mlmodel.star
files. Again, looking in the file itself may be easiest, or alternatively a plot may be made using the relion_star_plottable
script:
relion_star_plottable rootname_it000025_mlmodel.star data_mlmodel_classes rlnClassDistribution
Angular distribution
Per-image indicators
The _data.star
files store per-image indicators. Apart from the obvious orientational and class assignments, look out for the following variables:
_rlnLogLikeliContribution
: higher values mean better agreement between experimental data and model. This variable is the equivalent of the cross-correlation coefficient or phase residual in other programs. One could make histograms of all values in order to disard particularly bad images._rlnMaxValueProbDistribution
: values close to one indicate that the probability distributions over all orientations and classes have converged to near-delta functions. Values close to zero indicate great uncertainty in the assignments (i.e. near-even distributions). Typically, these values increase during multiple iterations (with constant sampling rates)