Metadata-Version: 2.2
Name: TaxSEA_in_python
Version: 0.1.4
Summary: A small package for converting bacterial names into NCBI IDs
Author-email: Cong Pham <phamleminhcong34@gmail.com>
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: pandas>=1.3.0
Requires-Dist: requests>=2.25.0
Requires-Dist: importlib-resources>=5.0.0
Requires-Dist: statsmodels>=0.14.4
Requires-Dist: numpy>=1.21.0

# TaxSEA_in_python project

This package is a version of TaxSEA but build in python. 

## Installation

```bash
pip install TaxSEA_in_python
```

## Usage

```python
# Import the Python-based implementation of TaxSEA, originally developed as an R tool.
from TaxSEA_in_python.TaxSEA import TaxSEA

# Locate the test data file within the package.
from importlib.resources import files 
TaxSEA_test_data = str(files('TaxSEA_in_python.data').joinpath('TaxSEA_test_data.csv'))

# Run the TaxSEA function on the test data.
# Optionally, you can specify an output location for the results by providing the `Output_location` argument.
# Example: TaxSEA(TaxSEA_test_data, Output_location='file/path')
TaxSEA_test_results = TaxSEA(TaxSEA_test_data)
print(TaxSEA_test_results)

# Access the three DataFrames returned in the TaxSEA_test_results dictionary.
Metabolite_producers = TaxSEA_test_results["Metabolite_producers"]
BugSigdB = TaxSEA_test_results["BugSigdB"]
Health_associations = TaxSEA_test_results["Health_associations"]
```
"""
