Skip to main content

A Graph-Based Approach to the Quality Threshold Clustering of Molecular Dynamics

Project description

BitQT

A Graph-Based Approach to the Quality Threshold Clustering of Molecular Dynamics

BitQT is a Python command-line interface (CLI) conceived to speed up the Heyer’s Quality Threshold (QT) clustering [1] of long Molecular Dynamics. The package implements a heuristic approach to this exact variant of QT.

BitQT Home Page

BitQT’s latest documentation, including usage examples, tutorials, benchmarks, etc., is available here.

Installation

There are some easy-to-install dependencies you must have before running BitQT. MDTraj (mandatory) will perform the heavy RMSD calculations, while VMD (optional) will help with visualization tasks. The rest of the dependencies (listed below) will be automatically managed by BitQT.

1. MDTraj

It is recommended that you install MDTraj using conda.

conda install -c conda-forge mdtraj

2. BitQT

  • Via pip

After successfully installing MDTraj, you can easily install BitQT and the rest of its dependencies using pip.

pip install bitqt

  • Via GitHub
git clone https://github.com/LQCT/bitqt
cd bitqt
python setup.py install

Then, you should be able to see BitQT help by typing in a console:

bitqt -h

3. VMD and VMD clustering plugin (optional)

BitQT clusters can be visualized by loading a .log file in VMD via a clustering plugin. Please see the VMD visualization tutorial in the BitQT documentation web page.

The official site for VMD download and installation can be found here.

Instructions on how to install the clustering plugin of VMD are available here.

Basic Usage

You can display the primary usage of BitQT by typing bitclust -h in the command line.

$ bitclust -h

usage: bitqt -traj trajectory [options]

BitQT: A Graph-based Approach to the Quality Threshold Clustering of Molecular
Dynamics

optional arguments:
  -h, --help           show this help message and exit

Trajectory options:
  -traj trajectory     Path to trajectory file [required]
  -top topology        Path to the topology file
  -first first_frame   First frame to analyze (counting from 0) [default: 0]
  -last last_frame     Last frame to analyze (counting from 0) [default: last
                       frame]
  -stride stride       Stride of frames to analyze [default: 1]
  -sel selection       Atom selection (MDTraj syntax) [default: all]

Clustering options:
  -cutoff k            RMSD cutoff [default: 2]
  -min_clust_size m    Minimum size of returned clusters [default: 2]
  -nclust n            Number of clusters to retrieve [default: 2]

Output options:
  -odir bitQT_outputs  Output directory to store analysis [default:
                       bitQT_outputs]

In the example folder, you can find a topology and trajectory files to run a bitqt test. Type the next command in the console and check if you can reproduce the content of the examples/output directory:

bitqt -traj aligned_original_tau_6K.dcd -top aligned_tau.pdb -cutoff 4 -odir outputs

Citation (work in-press)

If you make use of BitQT in your scientific work, cite it ;)

Release History

  • 0.0.1
    • First Release (academic publication)

Licence

BitQT is licensed under GNU General Public License v3.0.

Reference

[1] Heyer, L. J.; Kruglyak, S.; Yooseph, S. Exploring Expression Data Identification and Analysis of Coexpressed Genes. Genome Res. 1999, 9 (11), 1106–1115.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bitqt-0.0.2.tar.gz (12.1 kB view hashes)

Uploaded Source

Built Distribution

bitqt-0.0.2-py3-none-any.whl (22.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page