BooleaBayes
BoBa-T is a suite of network inference tools to derive and simulate gene regulatory networks from transcriptomics data; it is our single-cell update to BooleaBayes, which was published in PLOS Computational Biology, Wooten, Groves et al. (2019).
System Requirements
BoBa-T is compatible with Python 3.8 and above and runs on CPU hardware. It has been tested on Windows and macOS operating systems.
Dependencies
The graph-tool python package will need to be installed. This can be installed with Conda, homebrew, etc as seen here.
All other dependencies will be installed with this package and can be found within the setup.py file.
Installation Guide
To install boba-T, please use:
pip install bobaT
Typical install time is less than 1 minute on a standard laptop.
Instructions for Use:
The BoBa-T package is organized into the following modules:
net = make or modify network structure
load = loading data
proc = processing
rw = random walk
plot = plotting
tl = tools
utils = utilities
Demo:
For more details on how to use these functions, please see the tutorials for network construction (network_example.ipynb) and inference (inference_example.ipynb). These tutorials contain instructions to run the data, expected output, and explanations of the code. The network generation tutorial should run in less than 10 minutes on a standard laptop. The inference tutorial should run in less than 30 minutes on a standard laptop.
See this repository for examples and documentation of how to use this package.
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Metadata
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Release files for bobat 0.1.5
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Total release size: 111.5 kB
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| Tags | Python 3 |
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