Classification tutorial (EMPIAR-10304)

This tutorial shows how to convert raw tilt-series from EMPIAR-10304 (E. coli. ribosomes) into a ~4.9A resolution structure and resolve 8 different conformations.

Total running time required to complete this tutorial: 32 hrs.

We first use the command line to download and decompress a tbz file containing: 1) a script to download the raw tilt-series from EMPIAR, 2) corresponding metadata with tilt angles and acquisition order, and 3) an initial model:

# cd to a location in the shared file system and run:

tar xfz nextpyp_class_tutorial.tbz


Downloading the raw data from EMPIAR can take several minutes.

Open your browser and navigate to the url of your nextPYP instance (e.g.,

Step 1: Create a new project

Step 2: Import raw tilt-series

Step 3: Pre-processing

Step 4: Particle detection

Step 5: Reference-based refinement

Step 6. Filter particles

Step 7 (optional): Permanently remove bad particles

Step 8. Fully constrained refinement

Step 9: Create shape mask

Step 10. Region-based local refinement

Step 11: Particle-based CTF refinement

Step 12: Region-based refinement after CTF refinement

Step 13: 3D classification


Click on the round blue markers (top right of the page) to inspect different classes or go to the Class view or Classes Movie tabs to show all classes simultaneously


Running times were measured running all tilt-series in parallel on nodes with 124 vCPUs, 720GB RAM, and 3TB of local SSDs