Welcome to crYOLO’s User Guide!

Welcome, this is the user guide for crYOLO, an application for fast and accurate cryo-EM particle picking. It’s based on convolutional neural networks and utilizes the popular You Only Look Once (YOLO) object detection system.

• crYOLO makes picking fast – On a modern GPU it will pick your particles at up to 6 micrographs per second.

• crYOLO makes picking smart – The network learns the context of particles (e.g. not to pick particles on carbon or within ice contamination )

• crYOLO makes training easy – You might use a general network model and skip training completely. However, if the general model doesn’t give you satisfactory results or if you would like to improve them, you might want to train a specialized model specific for your data set by selecting particles (no selection of negative examples necessary) on a small number of micrographs.

• crYOLO makes training tolerant – Don’t worry if you miss quite a lot particles during creation of your training set. crYOLO will still do the job.

Note

Please read the Complimentary Science Software License before using crYOLO. If you are interested in using crYOLO in a commercial context please contact stefan.raunser@mpi-dortmund.mpg.de

User Guide: full table of contents

• Installation and Download
  • System requirements
  • Install crYOLO
  • Download the general models
• Tutorials
  • Tutorial 1: Pick particles without training using a general model
  • Tutorial 2: Pick particles by training a model for your data
  • Tutorial 3: Pick filaments using a model trained for your data
  • Tutorial 4: Pick particles using the general model refined for your data
  • Tutorial 5: Pick particles in tomograms
  • Tutorial 6: Pick filaments in tomograms
• Other pages
  • Complimentary Science Software License
  • crYOLO reference example
  • crYOLO configuration file
  • crYOLO on sparsely labeled data
  • crYOLO integration as Environment Module
  • crYOLO networks
  • Import crYOLO filament coordinates into Relion
  • Import coordinates into Relion 4
  • Import coordinates into cryoSPARC
  • General model data sets
  • Train your own general model
  • Train crYOLO based on good classes
• Changes
  • crYOLO
  • Boxmanager
• Troubleshooting
  • crYOLO is very slow and does not use the GPUs to the full potential
  • crYOLO crashed with glibc errors
  • crYOLO freezes
  • crYOLO has memory problems
  • I need more help

Part of

Citation

Main paper:

Wagner, T., Merino, F., Stabrin, M., Moriya, T., Antoni, C., Apelbaum, A., Hagel, P., Sitsel, O., Raisch, T., Prumbaum, D., Quentin, D., Roderer, D., Tacke, S., Siebolds, B., Schubert, E., Shaikh, T.R., Lill, P., Gatsogiannis, C., Raunser, S., 2019. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Commun Biol 2. https://doi.org/10.1038/s42003-019-0437-z

Filament picking:

Wagner, T., Lusnig, L., Pospich, S., Stabrin, M., Schönfeld, F., & Raunser, S. (2020). Two particle-picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER. Acta Crystallographica Section D Structural Biology, 76(7). https://doi.org/10.1107/s2059798320007342

Comment:

Wagner, T., Raunser, S. The evolution of SPHIRE-crYOLO particle picking and its application in automated cryo-EM processing workflows. Commun Biol 3, 61 (2020). https://doi.org/10.1038/s42003-020-0790-y

Help

Any questions? Problems? Suggestions?

Find help at our mailing list!

Indices and tables

• Search Page