Data

Tools

Indexes

Applications

Experiments

Open Source Science

pcaauto

PCAauto is a script developed to automate the PCA analysis of Molecular Dynamics.

https://github.com/brendaferrari/pcaauto

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.6%) to scientific vocabulary

Keywords

molecular-dynamics pca-analysis protein
Last synced: 6 months ago · JSON representation ·

Repository

PCAauto is a script developed to automate the PCA analysis of Molecular Dynamics.

Basic Info
  • Host: GitHub
  • Owner: brendaferrari
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 18.6 KB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 1
Topics
molecular-dynamics pca-analysis protein
Created over 3 years ago · Last pushed about 3 years ago
Metadata Files
Readme License Citation

README.md

🔴❗UNDER DEVELOPMENT❗🔴

Principal Component Analysis Automation (PCAauto)

PCAauto is a script developed to automate the PCA analysis of Molecular Dynamics.

Available methods are:

  • PCA analysis
  • Calculation of variance, cumulated varianc and explained variance (this last one only for 3 components for now)
  • Calculation of PCA through simulation time
  • Visualization o the movements of the components on model
  • Also, there is the possibility to plot graphs (under development)

Instalation

Download the code and unzip it on the desirable directory. To prepare the environment use the following command:

conda env create -f environment.yml

Be aware to uncomment the sections on the environment.yml file depending on which OS you are using.

How to use

Activate the environment using:

conda activate pca-mdaanalysis

You may modify the main.py file depending on which calculation you are interested.

The program uses a shell script to automate the calculation of data in multiple folders. To use this feature go to the root directory and on the terminal use:

bash \calculatePCA_inBulk.sh

If you are interested only on running one folder, you may just add your files to the PCAauto directory and use:

python calculatePCA.py

Observations

This script was developed following the MDA Analysis documentation, specifically the MDA Analysis examples page.

Authorship

Owner

  • Name: Brenda Ferrari
  • Login: brendaferrari
  • Kind: user

Chemistry PhD student - Python and Machine Learning student

Citation (CITATION.cff) 

cff-version: 0.0.1
message: "If you use this software, please cite it as below."
authors:
- family-names: "Ferrari"
  given-names: "Brenda"
  orcid: "https://orcid.org/0000-0001-5609-0947"
title: "PCAauto"
version: 0.0.1
doi: 10.5281/zenodo.7517294
date-released: 2023-01-09
url: "https://github.com/brendaferrari/PCAauto"

GitHub Events

Total
Last Year

Dependencies

environment.yml conda
  • matplotlib 3.5.2.*
  • mdanalysis 2.2.0.*
  • nglview 3.0.3.*
  • numpy 1.22.3.*
  • pandas 1.4.2.*
  • plotly 5.9.0.*
  • python 3.8.*
  • xlsxwriter 0.9.8.*