HA Trimer
Dataset
Learning objectives
We'll be taking a closer look into how to process a typical cryo-EM dataset from movies to a final result.
| Title | Value |
|---|---|
| Title | |
| Description | Leave empty |
| Directory | |
| Create Workspace | Enable |
| Workspace Title | Default |
| Parameter | Value |
|---|---|
| Movies data path | |
| Gain reference path | |
| Flip gain ref & defect file in Y? | Yes |
| Raw pixel size (A) | |
| Accelerating Voltage (kV) | |
| Spherical Aberration (mm) | |
| Total exposure dose (e/A^2) |
This should complete in under a minute.
Motion correction and CTF estimation scale well with the number of GPUs. We recommend using 4 GPUs for this tutorial.
| Parameter | Value |
|---|---|
| Number of GPUs to parallelize |
| Parameter | Value |
|---|---|
| Number of GPUs to parallelize |
Once interactive jobs such as exposure curation start to run, they will perform a number of processing steps and then wait for user input.
Select all exposures with a maximum CTF Fit Resolution (A) of 6A.
| Parameter | Value |
|---|---|
| Minimum particle diameter (A) | |
| Maximum particle diameter (A) | |
| Use elliptical blob | Yes |
Inspect Picks outputs filtered pick locations so it's easier to compare and visualize different sets of picks at various thresholds. When you're happy with the set of particle locations, continue to the extraction phase to generated a set of particle images (a particle stack).
Select pick locations with an NCC >= 0.2 and Power Score > 824 and < 2955.
You should end up with around 65K particle locations.
| Parameter | Value |
|---|---|
| Number of CPU cores | |
| Extraction box size (pix) |
As of CryoSPARC v4.3, 2D Classification works best with 1-2 GPUs. If you have more GPUs you'd like to utilize, we recommend running multiple 2D Classification jobs in parallel, each with tweaks to key parameters such as the number of classes. Typically these results provide much more information about a dataset rather than have a single job run a bit quicker.
| Parameter | Value |
|---|---|
| Number of GPUs to parallelize |
Choose a set of 2D classes that look sharp and display secondary structure features.
You should end up with around 35K particles.
Use default parameters
| Parameter | Value |
|---|---|
| Symmetry |
Final Result
You should have a 3D reconstruction of the HA Trimer at ~3.4A resolution.