relion-yolo-it 0.2.9

Updated relion_it with cryolo wrappers

relion_it with crYOLO support

relion_it is now running with python 3.6.8! In options you can choose to pick via the crYOLO general model or with the relion auto picker. CrYOLO runs as an external job after ctfFind. Relion then takes the particle coordinates found by crYOLO and then further processes them. Particles appear as a manual pick job in the relion gui and can be viewed there.

Requirements for external use:

1. CrYOLO and Relion 3.0 installed.

2. Conda Environment for crYOLO and Relion

3. Edit paths in options.py for MotionCor2 and Cryolo general model locations

4. Run by: cryolo_relion_it.py /Path/To/options.py --gui

Scripts being used:

• cryolo_relion_it.py: The main script that dls_yolo_relion calls. This houses the main pipeline and calls to all the other scripts.

• CryoloPipeline.py: The crYOLO pipeline. This runs as a subprocess and exectutes many repeated times to Import, MotionCorr, CtfFind, crYOLO pick, Extract... as new movies are collected. As Relion 3.0 does not support external job types the YOLO pipeline is in fact 3 seperate pipelines chained together.

• CryoloExternalJob.py: Reads Relion star files and makes a directory that crYOLO can execute particle picking from.

• CorrectPath.py: After crYOLO has picked particles, the coordinate star files must be placed in a directory tree that Relion is expecting. This does that!

• CryoloFineTuneJob.py: After 2D classification, good classes can be selected to fine tune the cryolo general model. After the finetuning, crYOLO uses this new model to pick future particles in the current run.

• options.py: Basic options for relion_it to run with.

• qsub.sh: Cluster submit script for crYOLO.

• qtemplate.sh: Cluster template for crYOLO. If using cluster must have template create a '.cry_predict_done' file so that the pipeline knows that cryolo has finished.

Note: Fine-tuning requires good 2D classes to be picked by hand after first 2D iteration