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
Files:
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Abe KM, Li G, He Q, Grant T, Lim CJ. (2024)
Fenn KL, Horne JE, Crossley JA, Böhringer N, Horne RJ, Schäberle TF, Calabrese AN, Radford SE, Ranson NA. (2024)
Hicks CW, Rahman S, Gloor SL, Fields JK, Husby NL, Vaidya A, Maier KE, Morgan M, Keogh MC, Wolberger C. (2024)
Gusach A, Lee Y, Khoshgrudi AN, Mukhaleva E, Ma N, Koers EJ, Chen Q, Edwards PC, Huang F, Kim J, Mancia F, Veprintsev DB, Vaidehi N, Weyand SN, Tate CG. (2024)
Kofler L, Grundmann L, Gerhalter M, Prattes M, Merl-Pham J, Zisser G, Grishkovskaya I, Hodirnau VV, Vareka M, Breinbauer R, Hauck SM, Haselbach D, Bergler H. (2024)