本家様 https://github.com/kiharalab/CryoREAD

Cryo_READ is a computational tool using deep learning to automatically build full DNA/RNA atomic structure from cryo-EM map.

deepL先生日本語訳
【Cryo_READは、低温電子顕微鏡マップからDNA/RNAの完全な原子構造を自動的に構築するディープラーニングを用いた計算ツールである。】

インストール

condaアプリのようなので、いつものように pyenv-anaconda環境にて CryoREAD 実行環境を作ります

既にpyenv-anaconda環境があれば別ですが、なければ

git clone https://github.com/yyuu/pyenv.git /apps/pyenv
export PYENV_ROOT=/apps/pyenv
export PATH=$PYENV_ROOT/bin:$PATH
 
pyenv install miniforge3-23.11.0-0
source /apps/pyenv/versions/miniforge3-23.11.0-0/etc/profile.d/conda.sh

とします。
既にあれば

source /apps/pyenv/versions/miniforge3-23.11.0-0/etc/profile.d/conda.sh

で準備して、

[root@rockylinux ~]# cd /apps/
 
[root@rockylinux apps]# git clone https://github.com/kiharalab/CryoREAD
 
[root@rockylinux apps]# cd CryoREAD/
 
[root@rockylinux CryoREAD]# conda env create -f environment.yml
 
[root@rockylinux CryoREAD]# conda activate CryoREAD
 
(CryoREAD) [root@rockylinux CryoREAD]# which python
/apps/pyenv/versions/miniforge3-23.11.0-0/envs/CryoREAD/bin/python
 
(CryoREAD) [root@rockylinux CryoREAD]# 
(CryoREAD) [root@rockylinux CryoREAD]# python ./main.py -h
usage: main.py [-h] [-F F] [-M M] [-P P] [--output OUTPUT] --mode MODE [--contour CONTOUR] [--stride STRIDE] [--box_size BOX_SIZE] [--gpu GPU]
               [--batch_size BATCH_SIZE] [-f F] [-m M] [-g G] [-k K] [-R R] [--rule_soft RULE_SOFT] [--frag_size FRAG_SIZE] [--frag_stride FRAG_STRIDE]
               [--top_select TOP_SELECT] [--resolution RESOLUTION] [--num_workers NUM_WORKERS] [--prediction_only] [--no_seqinfo] [--refine] [--colab]
               [--thread THREAD]
 
optional arguments:
  -h, --help            show this help message and exit
  -F F                  Input map file path. (str)
  -M M                  Pre-trained model path. (str) Default value: "best_model"
  -P P                  Optional fasta sequence file path. (str)
  --output OUTPUT       Output directory
  --mode MODE           Control Mode for program: 0: cryo_READ structure modeling. Required parameter. (Integer), Default value: 0
  --contour CONTOUR     Contour level for input map, suggested 0.5*[author_contour]. (Float), Default value: 0.0
  --stride STRIDE       Stride for scanning of deep learning model. (Integer), Default value: 32.
  --box_size BOX_SIZE   Input box size for deep learning model. (Integer), Default value: 64
  --gpu GPU             Specify the gpu we will use. (str), Default value: None.
  --batch_size BATCH_SIZE
                        Batch size for inference of network. (Integer), Default value: 8.
  -f F                  Filter for representative points, for LDPs, removing points' normalized density<=-f (Float), Default value: 0.05
  -m M                  After meanshifting merge points distance<[float]. (Float), Default value: 2.0.
  -g G                  Bandwidth of the Gaussian filter, (Float), Default value: 3.0.
  -k K                  Always keep edges where d<k parameter. (Float), Default value: 0.5
  -R R                  Maximum length of local edges. (Float), Default value: 10.0.
  --rule_soft RULE_SOFT
                        Use strict/soft rules to assemble collected fragments in DP step. (Integer), Default value: 0 (strict rules)
  --frag_size FRAG_SIZE
                        Fragment size for sequence split.(Integer), Default value: 20
  --frag_stride FRAG_STRIDE
                        Frag stride step. (Integer), Default value: 2
  --top_select TOP_SELECT
                        Select top fragment candidate here. (Integer), Default value: 20
  --resolution RESOLUTION
                        resolution of maps, used for final structure refinement. (Float), Default value: 2.5
  --num_workers NUM_WORKERS
                        number of workers to fetch data for GPU inference. (Integer), Default value: 4
  --prediction_only     Optional input. Only run the deep learning prediction step. (True/False) Default value: False
  --no_seqinfo          Optional input. Build structures when no sequence information is available. (True/False) Default value: False
  --refine              Optional Input. Use Phenix to do the last step refinement or not (Suggested to set as True).
  --colab               Optional Input. Used to specify the phenix path for colab settings
  --thread THREAD       Use multiple threads for fragment-based sequence assignment,default:1 (multi-threading is disabled)
(CryoREAD) [root@rockylinux CryoREAD]#

EnvironmentModules

「/apps/modulefiles/CryoREAD」

#%Module1.0
 
set root /apps/pyenv/versions/miniforge3-23.11.0-0/envs/CryoREAD
 
prepend-path PATH   $root/bin:/apps/CryoREAD
[saber@rockylinux ~]$ module use /apps/modulefiles/
[saber@rockylinux ~]$ module load CryoREAD
 
[saber@rockylinux ~]$ python /apps/CryoREAD/main.py
usage: main.py [-h] [-F F] [-M M] [-P P] [--output OUTPUT] --mode MODE [--contour CONTOUR] [--stride STRIDE] [--box_size BOX_SIZE] [--gpu GPU]
               [--batch_size BATCH_SIZE] [-f F] [-m M] [-g G] [-k K] [-R R] [--rule_soft RULE_SOFT] [--frag_size FRAG_SIZE] [--frag_stride FRAG_STRIDE]
               [--top_select TOP_SELECT] [--resolution RESOLUTION] [--num_workers NUM_WORKERS] [--prediction_only] [--no_seqinfo] [--refine] [--colab]
               [--thread THREAD]
main.py: error: the following arguments are required: --mode
[saber@rockylinux ~]$

となるが、面倒なので「/apps/CryoREAD/main.py」の行頭を変更

[root@rockylinux ~]# vi /apps/CryoREAD/main.py
#!/apps/pyenv/versions/miniforge3-23.11.0-0/envs/CryoREAD/bin/python
 
import os
import mrcfile
import numpy as np
 :
 :
[root@rockylinux ~]#
[root@rockylinux ~]# chmod +x /apps/CryoREAD/main.py
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Last-modified: 2024-05-30 (木) 15:24:22