CryoEM scripts

The scripts in this repository are currently not maintained and may be outdated. Some of the functionality I use regularly can be found in the following tools, that I still maintain:

• topaztrainmetric
• countparticles
• classconvergence
• angdist
• localres

Various utilities to help cryoEM data analysis

Available utilities so far:

• count_particles.awk: count particles contributing to each class of a class2D or class3D job from RELION, by reading a run_it*_data.star file. Dependencies: awk. automatically apply it to all *_data.star files in the current directory and
• multi_count_particles.sh: loop wrapper for count_particles.awk, to save results in tsv files. Dependencies: bash, count_particles.awk.
• monitor_relion_classification.R: plot number of particles as a function of iteration number for each class of a RELION class2D or class3D job, reading the summary files from multi_count_particles.sh. Dependencies: R, Tidyverse, multi_count_particles.sh.
• dm4_to_mrc.sh: convert a dm4 file to mrc format (useful to convert gain reference images to a format MotionCor2 can read). Dependencies: bash, EMAN2.
• star2box.awk: convert particle coordinates from RELION *pick.star format to EMAN2 .box format. Dependencies: awk.
• setup_cryolo.sh, run_cryolo_training.sh, run_cryolo_picking.sh, cryolo_config.json, run_janni_denoise.sh: set up a directory structure to train and/or perform particle picking with crYOLO. Dependencies: bash, crYOLO.
• randomly_pick_micrographs.py: select a random subset of micrographs to constitute a training set for crYOLO. Dependencies: Python3, numpy.
• imgstats.sh: gather pixel intensity statistics from motion-corrected micrographs. Dependencies: IMOD.
• exclude_low_res_micrographs.awk: filter a micrographs_ctf.star file from RELION to keep only micrographs with a rlnCtfMaxResolution equal to or better than a user-provided threshold. Dependencies: awk.