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.
Metadata
Release files for bitqt 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| bitqt-0.0.2.tar.gz | 12.1 kB | Without provenance | Details for bitqt-0.0.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| bitqt-0.0.2-py3-none-any.whl | Python 3 | none | any | Details for bitqt-0.0.2-py3-none-any.whl |
Total release size: 34.6 kB
Release files / bitqt-0.0.2.tar.gz
| Download URL | bitqt-0.0.2.tar.gz |
|---|---|
| Size | 12.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
be7ba7f3e5cd4a7d9fb3571d6505662c9dc57ea901d0a1c9cb7ebde90c8aaaa3
|
|
BLAKE2b-256 checksum How to use checksums |
512f99b04f5368d127b64235c2c9835fb3282ce03c482ee2e94dd5bcffecf292
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.7.0 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8
|
Release files / bitqt-0.0.2-py3-none-any.whl
| Download URL | bitqt-0.0.2-py3-none-any.whl |
|---|---|
| Size | 22.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8abd59ca590f42cd47b9fcfda68f81da4892b8d06db8b906504bffd146389d1f
|
|
BLAKE2b-256 checksum How to use checksums |
14e5bf141f6ab2091a7a3a413eb5005dc5b5a669d99e5b8befc7242d5845bd81
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.7.0 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8
|
Security for bitqt 0.0.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.