Protein Functional Domain Analysis based on Compressed Sparse Matrix
Project description
## ProdMX : Protein Functional Domain based on Compressed Sparse Matrices
ProdMX is a tool with user-friendly utilities developed to facilitate high-throughput analysis of protein functional domains and domain architectures. The ProdMX employs a compressed sparse matrix algorithm to reduce computational resources and time used to perform the matrix manipulation during functional domain analysis.
### Dependencies
- Python 3.5 or newer and the following packages:
[pandas](https://github.com/pandas-dev/pandas)
[h5py](https://github.com/h5py/h5py)
[numpy](https://github.com/numpy/numpy)
[tqdm](https://github.com/tqdm/tqdm)
[scipy](https://github.com/scipy/scipy)
### Installation from source
` git clone https://github.com/visanuwan/prodmx python -m pip install prodmx ` ### Usage
Generally, the use of the ProdMX tool starts with constructing the compressed sparse matrix of either protein functional domains or domain architectures in a command-line environment. The input of ProdMX is a tab-delimited file containing two columns of genome labels and the path to their HMMER results.
Protein functional domain
` prodmx-buildDomain [-h] [-v] [-i INPUT] [-o OUTPUT] [-k] `
Domain architecture
` prodmx-buildArchitecture [-h] [-v] [-i INPUT] [-o OUTPUT] [-k] ` For the detail of commands and examples, see the example of analyses using ProdMX in [Jupyter Notebook.](test/prodmx_example.ipynb)
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