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Relion 3D refinement

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Michael A. Cianfrocco edited this page Jun 7, 2018 · 1 revision

Home > 3D classification & refinement > Relion 3D refinement

##Relion 3D refinement

Now that you have performed 3D classification, you will select a single class (or multiple classes) that are considered to be 'homogenous' and will refine them further in an exhaustive manner. This will help you to achieve a higher resolution structure than that previously generated during 3D classification.

3D refinement in Relion pushes your data to its limit, helping to get to the highest resolution possible.

This procedure can run on CTF-uncorrected or CTF-corrected data. Commonly, negative stain data will not be CTF corrected, but cryo-EM data will be CTF-corrected.

The following steps outline the options needed to input into the Relion GUI.

  1. Inputs for 3D refinement in Relion
  2. Selecting particles that belong to a specific class after 3D classification
  3. Launching & using Relion's GUI
  4. Submitting job to cluster
  5. Example cluster submission script
  6. Outputs
  7. Continuing stopped Relion run

####Inputs for 3D refinement in Relion

You will need a .star file for the input particles that will be refined. This can be the original .star file that contains all of your particles or it could be a subset that you have selected because they belong to a homogenous class that resulted from 3D classification (see below).

  • .star file generated with per-particle CTF and micrograph information. This is named [rootname].star by the extraction step.
  • .mrcs and .star files for each micrograph within the folder Particles/Micrographs

####Selecting particles that belong to a specific class after 3D classification

You can use Relion's 'Display' feature within the Relion GUI to select particles that below to a certain class after 3D classification finishes. This would be useful if you had only one or two classes after 3D classification that were homogenous and warranted further refinement.

First, find the _model.star file associated with the iteration of 3D classification that you liked the most. For example, the 22nd iteration of this 3D classification looked the best:

Class3D/run1_it022_model.star

Select this file using the Relion 'Display' feature.

Then, the following window will display a single slice through each volume. Select the class(es) that you like by left clicking with your mouse (you'll see a red box appear about around the classes that you selected). Then, click click one of these selected classes and choose SAVE star with particles from selected classes:

Now,specify an output name for this .star file. In order to keep everything straight, naming the selected file the same base name as original file but with a suffix like '_class3.star' is helpful.

####Launching & using Relion's GUI

$ relion &

Which will open this window:

  • Input pixel size for your data. This will need to be adjusted to a new pixel size if you binned your data during extraction
  • The diameter selected must extend beyond the protein density that you expect, but if it is too wide, you may include too much information and lead to artifacts during analysis.

Now, click on the 3D auto-refine tab on the left hand list. You will need to enter the following inputs:

  • Particle star file - This should be the 'selected' star file from above, or the originally extracted particle star file
  • Output rootname - The output rootname for this refinement. It will be written into a folder named 'Refine3D'

Clicking onto the next tab, Reference, you will provide inputs for the 3D model that you will use as an initial model:

  • Reference map - This should be a volume from one of the selected classes from 3D classification.
  • Greyscale? - If you are using a 3D volume from 3D classification, then the answer to this question is 'Yes'. Otherwise, 'No'.
  • Initial low-pass filter - For 3D classification and refinement, it is important to input a filtered 3D model in order to avoid model bias. This means that you can 1) filter your model outside of Relion or 2) you could filter it using Relion as specified here. You should filter your model to 50 - 60 Angstroms to prevent model bias.
  • Symmetry - Input symmetry for your molecule. Asymmetric single particles are 'C1'.

Clicking onto the next tab, CTF, you will decide if you are correcting the CTF of your model:

  • CTF - correction? - You can only perform CTF correction if you extracted particles using Relion with CTFFIND3 input log files. CTF-correction is recommended for cryo-EM data, and is not necessary for negative stain data.
  • Has reference been CTF corrected? - If the 3D model came from Relion as a CTF-corrected output model, then you can answer 'Yes' to this question. Otherwise, 'No'.
  • Have data been phase-flipped? - If you are analyzing negative stain data without CTF-correction, you can input phase flipped particles here and answer 'Yes' to this question. Normally, the answer is 'No'.
  • Ignore CTFs until first peak? - In case the CTF confidence is low for only low-resolution information, then you could set this to 'Yes'. Generally, this is not a problem and we have not seen anyone need to use this option.

Clicking through to the Optimisation tab, you will input options for the 3D refinement run:

  • Mask particles with zeros? - This will mask the particle data outside of the given radius to a value of 0. This will help to prevent overalignment of particles to background noise.
  • Reference mask - The reference mask is a shape with the value of '1' on the inside of the mask and '0' on the outside of the mask. This is very similar to 'solvent flattening' in X-ray crystallography. If you know the shape of your sample very well, then you can exclude all data that falls outside of a given mask.

The last tab to use is the Auto Sampling tab:

  • Angular sampling interval - Auto-refine will perform auto sampling during refinement, which means that it will use angular steps that are dictated by the given resolution of your 3D model. So, no need for input here.
  • Offset search range - This value specifies a radius over which the model will search for the center of the particles selected. In principle, if all particles were centered perfectly, then there would be no need for a search range. But, inevitably particles are off-center by a few pixels and this will correct for this.
  • Offset search step - While searching through the search range, Relion will incrementally search at defined distances away from the center of the image. This increment is defined here as the 'step' of the searching.
  • Local searches from auto-sampling? - This default value works for all projects, leave as is.

At this point, you can can click 'Just show command' and it will output a command that looks like:

 *** The command is:
`which relion_refine_mpi` --o Refine3D/run1 --auto_refine --split_random_halves --i particles_sel.star --particle_diameter 200 --angpix 1 --ref Class3D/run1_iter022_class1.mrc --ini_high 60 --ctf --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --auto_local_healpix_order 4 --offset_range 5 --offset_step 2 --sym C1 --low_resol_join_halves 40 --norm --scale  --j 1 --memory_per_thread 4

####Submitting job to cluster

Depending on your specific cluster setup, these details will change. But, generally, you will need to place this Relion command into a shell script that can be submitted to your cluster (or the cloud) so that it can run over 100+ CPUs.

Most clusters will use a job submission script like Sun Grid Engine (Oracle), where you can submit a text file using the 'qsub' command:

$ qsub relion3d_refine_submit.run

And then you can monitor the outputs into the folder Refine3D.

####Example cluster submission script

Here is an example of a cluster submission script:

#!/bin/csh

#Wall time in seconds
#$ -l h_rt=3600,m_mem_free=4g 

#Name of job
#$ -N submitrelionrefine3D

#Use current working directory
#$ -cwd 

#Use verbose output
#$ -V

#Number of CPUs
#$ -N 120

#Submission command

mpirun -np $NSLOT relion_refine_mpi --o Refine3D/run1 --auto_refine --split_random_halves --i particles_sel.star --particle_diameter 200 --angpix 1 --ref Class3D/run1_iter022_class1.mrc --ini_high 60 --ctf --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --auto_local_healpix_order 4 --offset_range 5 --offset_step 2 --sym C1 --low_resol_join_halves 40 --norm --scale  --j 1 --memory_per_thread 4

####Outputs

As Relion runs on your cluster, there will be text output to the standard out files, which includes information that will look like this:

Auto-refine: Angular step= 3.75 degrees; local searches= false
 Auto-refine: Offset search range= 6.5 pixels; offset step= 1.5 pixels
 CurrentResolution= 18.6 Angstroms, which requires orientationSampling of at least 12.8571 degrees for a particle of diameter 160 Angstroms
 Oversampling= 0 NrHiddenVariableSamplingPoints= 479232
 OrientationalSampling= 7.5 NrOrientations= 36864
 TranslationalSampling= 3 NrTranslations= 13

For each iteration that it completes, there will be five files. For example, iteration 22 for run1:

  • Refine3D/run1_iter022_half1_class001.mrc - 3D volumes for each half volume, where the half volumes are used for the FSC curve calculation
  • Refine3D/run1_iter022_half1_class00?_angdist.bild - A file that shows a 3D histogram of each euler angle direction used for the 3D model. Open in UCSF Chimera along with the 3D model to make sure that there are not any overrepresented classes used in the 3D reconstruction.
  • Refine3D/run1_iter022_half1_class001.mrc - 3D volumes for each half volume, where the half volumes are used for the FSC curve calculation
  • Refine3D/run1_iter022_half1_class00?_angdist.bild - A file that shows a 3D histogram of each euler angle direction used for the 3D model. Open in UCSF Chimera along with the 3D model to make sure that there are not any overrepresented classes used in the 3D reconstruction.
  • Refine3D/run1_iter022_data.star - text file with per-particle CTF/score information
  • Refine3D/run1_iter022_half?_model.star - STAR file that should be opened in Relion to view 3D models
  • Refine3D/run1_iter022_optimiser.star - STAR file with 3D classification information
  • Refine3D/run1_iter022_sampling.star - STAR file with 3D classification information

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