Job: Homogeneous Ab-Initio Refinement (BETA)

At a Glance

Use CryoSPARC's ab-initio algorithm (based on stochastic gradient descent) to refine a dataset to high resolution from scratch, while preserving gold standard independence of two half-sets and half-maps.

Description

Homogeneous Ab-Initio Refinement should generally be tried only once traditional global refinements fail to produce reasonable results. See Recommended Alternatives for more information.

In some challenging cases, refinement of a 3D map to high resolution using CryoSPARC's gradient descent algorithm for ab-initio reconstruction outperforms the traditional expectation maximization algorithm used in refinement jobs [1]. However, directly using the Ab-Initio Reconstruction job to produce high-resolution volumes makes resolution estimation and validation difficult, since Ab-Initio Reconstruction does not use gold standard half-sets.

New in CryoSPARC v5.0, This job splits input particles into two half-sets and refines independent half-maps each using the same process as Ab-Initio Reconstruction. Notably, this job is still ab-initio in that it does not use any input volume; both half maps are reconstructed independently from scratch from the data alone, and kept aligned to each other by a 3D map alignment step within the job. This job can only produce a single homogeneous output rather than multiple classes.

The output half-maps can be further refined downstream using Local Refinement which can sometimes further improve map quality. Note that using a global refinement downstream, like Homogeneous or Non-Uniform Refinement, typically will not yield results superior to using standard Ab-initio Reconstruction followed by refinement.

Inputs

Particle stacks

Particles from which half maps will be produced.

Commonly Adjusted Parameters

See Ab-Initio Reconstruction for parameter information.

Outputs

Particles

Particles with poses and half-set splits used to produce the half maps.

Volumes

Unlike other refinement jobs in CryoSPARC, Homogeneous Ab-Initio Refinement produces only half maps.

Unused particles

Particles which were not used. This typically means that the refinement converged before all particles had been aligned. If you wish to align all particles, set Num particles to use to a value greater than or equal to the number of input particles.

Common Next Steps

To produce an averaged, filtered full map you can either use Homogeneous Reconstruction Only with the particles output, or use the particles and half maps in Local Refinement with Initialize from input half-maps turned on.

Recommended Alternatives

Homogeneous Ab-Initio Refinement currently requires far more iterations than other techniques to produce a final map. For this reason, this job should only be used when both:

• Particle images produce high-quality 2D classes, indicating that real signal is present in the particle stack

• Global refinements of particles (e.g., Homogeneous or Non-Uniform Refinement) produce maps with a quality much worse than expected based on 2D Classification results

References

1. Kookjoo Kim, Huan Li, Oliver B. Clarke (2025). High-resolution ab initio reconstruction enables cryo-EM structure determination of small particles. bioRxiv 2025.09.08.674935; doi: https://doi.org/10.1101/2025.09.08.674935