EMPIAR-10812
Training data set for automated 2D class selection [18051 class averages in MRCS format]
Publication:

New tools for automated cryo-EM single-particle analysis in RELION-4.0

Kimanius D, Dong L, Sharov G, Nakane T, Scheres SHW

The Biochemical journal 478 (2021) 4169-4185

PMID: 34783343

Related EMDB entry:
Deposited:
2021-09-20
Released:
2021-10-01
Last modified:
2022-02-28
Imageset size:
20.74 GB
Imageset DOI:
Experimental metadata:
Download xml json
Contains:
  • class averages
1. 2D class averages for training neural network in region_class_ranker
Category:
class averages
Image format:
MRCS
No. of images or tilt series:
18051
Image size:
(None, None)
Pixel type:
32 BIT FLOAT
Pixel spacing:
(None, None)
Details:
Each subdirectory with 12 random characters contains a single 2D classification run, with an image file run_class.mrcs that contains the actual 2D class averages, the files run_model.star, run_data.star, run_sampling.star and run_optimiser.star with the corresponding metadata from RELION's 2D classification run (see RELION documentation for details), a file job_score.txt that contains the manually assigned job score for that 2D classification run, a backup_selection.star file that contains the different categories of assigned classes, which are converted to individual class scores in the class_ranker program (see function ClassRanker::getClassScoreFromJobScore inside src/class_ranker.cpp), and a file features_normalized.star that contains the features calculated by the region_class_ranker program.

One can visualise the images for each class, e.g. in directory cahg4Zo4Goos, with the following command:

relion_display --sort rlnClassDistribution --reverse --class --i cahg4Zo4Goos/run_optimiser.star --fn_imgs cahg4Zo4Goos/backup_selection.star

Classes shown in red (1 in backup_selection.star) are the best according to the manually assigned class labels in backup_selection.star; magenta (5) are second-best; green (2) third-best; and blue (3) or cyan (4) fourth-best. Yellow classes (6) or non-coloured classes (0) are the worst (score=0).

The normalised_features.star file was calculated in RELION-4.0, running the following command in csh from the main directory:

foreach opt (*/run_optimiser.star)
set dir=`echo ${opt} | awk -F"/" '{print $1}'`
echo $dir
relion_class_ranker --train --do_granularity_features --extract_subimages --subimage_boxsize 64 --nr_subimages 25 --opt ${dir}/run_optimiser.star --select ${dir}/backup_selection.star --fn_score ${dir}/job_score.txt --o ${dir} --write_normalized_features
end
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