NT-193

Author: rei-ashine
DATE: Oct. 10th, 2023
UPDATE: Oct. 30th, 2023

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Scripts for

1. Formatting a PDB file
   USAGE: bash 01_format_pdb_files.sh &>> logs/formatting.log
   [NOTE]: Before running the shell script,
   you should do cp config.sample config and change the path
   to the directory containing the pdb files you want to format in the config file.

2. Creating scatter plots from PISA score CSV files
   USAGE: bash 02_visualize_pisa_scores.sh &>> logs/visualizing.log
   [NOTE]: Before running the shell script,
   you should change the path to the directory containing
   the PISA score CSV files you want to visualize in the config file.

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Installing Dependencies

All dependencies can be installed with conda.
An environment screenshot is provided :

conda env create -f environment.yml

Once the environment is created,
it can be used at any time (without having to download everything again) :

conda activate nt-193

Exit the running virtual environment :

conda deactivate

Delete the virtual environment :

conda remove -n nt-193 --all

Setting up Jupyter Notebook

Add a virtual environment to the kernel of Jupyter Notebook :

ipython kernel install --user --name nt-193

Confirm that "nt-193" is included in "Available kernels" :

jupyter kernelspec list

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Antibody Residue Modification Protocol

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Directory Structure

.
├── README.md
├── 01_format_pdb_files.sh
├── 02_visualize_pisa_scores.sh
├── Jupyter-Notebooks
│   └── visualize_PISA_scores.ipynb
├── commands
│   └── PyMOL
├── data
│   ├── 7E5O
│   ├── Formatted
│   ├── MolDesk
│   ├── PISA
│   ├── PNG
│   ├── GoogleSheets
│   ├── PDBsum
│   └── PyMOL
├── logs
│   ├── DUMP
│   ├── formatting.log
│   └── visualizing.log
├── scripts
│   ├── DUMP
│   ├── format_pdb_file.py
│   ├── format_pisa_data.gs
│   └── visualize_pisa_scores.py
├── DUMP
├── config
├── config.sample
└── environment.yml

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Statistics

===============================================================================
 Language            Files        Lines         Code     Comments       Blanks
===============================================================================
 Python                  4          412          291           35           86
 Shell                   6          177          111           42           24
 Plain Text              5          246            0          201           45
 YAML                    1           24           24            0            0
-------------------------------------------------------------------------------
 Jupyter Notebooks       1            0            0            0            0
 |- Markdown             1            8            0            7            1
 |- Python               1          148          103           22           23
 (Total)                            156          103           29           24
-------------------------------------------------------------------------------
 Markdown                1           51            0           44            7
 |- BASH                 1            6            6            0            0
 (Total)                             57            6           44            7
===============================================================================
 Total                  18          910          426          322          162
===============================================================================