Metadata-Version: 2.4
Name: anbiopy
Version: 0.1.3
Summary: Python package designed for the analysis of microbiota data when incorporating other types of variables e.g., anthropometric
Project-URL: Homepage, https://github.com/juanspardor/anbiopy
Project-URL: Issues, https://github.com/juanspardor/anbiopy/issues
Author-email: Juan Sebastian Pardo <j.pardor@uniandes.edu.co>
License-Expression: MIT
License-File: LICENSE
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-bio
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: statsmodels
Description-Content-Type: text/markdown

# Amapy Library

Author: Juan Sebastián Pardo
License: MIT License

## Introduction
anbiopy is a Python library designed for microbiota data analysis. It is specifically intented to use when users have the following data:
- OTU observations
- OTU taxonomy
- OTU Tree
- Any kind of anthropometric or additional data

Based on these, anbiopy is able to assist users in analyzing microbiota data and possible relationships with anthropometric variables e.g., alpha diversity vs height/weight/sex/etc. 


## Library Components
anbiopy consists of 3 categories of analysis: 
1. Basic microbiota analysis
2. Graphic analysis
3. Numeric analysis

In the following segments we will go through the functionalities of each component using examples. 

## Installation
Using `pip`
```bash
pip install anbiopy
```

## Dependencies
This library is built using:
- pandas
- numpy
- matplotlib
- seaborn
- scipy
- scikit-learn
- statsmodels
- scikit-bio

All these dependencies should be installed along with anbiopy
