Calculate NPR values & Generate Heatmap: Difference between revisions

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  (base)$ conda create -c rdkit --name npr-py3 rdkit
  (base)$ conda create -c rdkit --name npr-py3 rdkit
  (base)$ conda activate npr-py3
  (base)$ conda activate npr-py3
# Install jupyter notebook
(npr-py3)$ conda install -c conda-forge notebook
  # Install vaex - dataframe library for huge libraries
  # Install vaex - dataframe library for huge libraries
  (npr-py3)$ conda install -c conda-forge vaex  
  (npr-py3)$ conda install -c conda-forge vaex
   
  (npr-py3)$ pip install ipython==7.9.0
 
=== Run NPR calculation ===
=== Run NPR calculation ===
Your smiles file should be format like this
Your smiles file should be in this format with no header: <smiles> <cid>
(npr-py3)$ python extra_newprops.py {smiles_file}
Notes:


'''<smiles> <cid>'''
- Failed and success molecules are output from this script.
(npr-py3)$ python extra_newprops.py {smiles_file}
 
- The calculation maybe slow. It is recommend that you chunk the file and run it on parallel.


== Make Heatmap ==
== Make Heatmap ==
=== Generate h5py binary file ===
(npr-py3)$ python py_csv2hdf5.py {output_smiles_file}
This script without output h5py that is then can be read by vaex library (it is useful for read huge library into dataframe)
=== Plot ===
# Run Jupyter-Notebook
(npr-py3)$ jupyter-notebook
From jupyter-notebook interface
- Select 'single_plot.ipynb'
- Change the path to h5py file and run the kernel

Latest revision as of 07:49, 5 November 2020

Calculate NPR

Setup Python environment

- Download Anaconda3 installer and install follow the instruction (https://www.anaconda.com/products/individual) - Create anaconda env and install packages

(base)$ conda create -c rdkit --name npr-py3 rdkit
(base)$ conda activate npr-py3
# Install vaex - dataframe library for huge libraries
(npr-py3)$ conda install -c conda-forge vaex
(npr-py3)$ pip install ipython==7.9.0

Run NPR calculation

Your smiles file should be in this format with no header: <smiles> <cid>

(npr-py3)$ python extra_newprops.py {smiles_file}

Notes:

- Failed and success molecules are output from this script.

- The calculation maybe slow. It is recommend that you chunk the file and run it on parallel.

Make Heatmap

Generate h5py binary file

(npr-py3)$ python py_csv2hdf5.py {output_smiles_file}

This script without output h5py that is then can be read by vaex library (it is useful for read huge library into dataframe)

Plot

# Run Jupyter-Notebook
(npr-py3)$ jupyter-notebook

From jupyter-notebook interface

- Select 'single_plot.ipynb'

- Change the path to h5py file and run the kernel