https://github.com/muhammedhasan/betabinomial

Beta-Binomial for testing count data
https://github.com/muhammedhasan/betabinomial

count inference python statistics

Last synced: about 1 month ago
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Beta-Binomial for testing count data

• Host: GitHub
• URL: https://github.com/muhammedhasan/betabinomial
• Owner: MuhammedHasan
• Created: 2022-02-17T20:26:23.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2023-01-11T02:34:34.000Z (almost 2 years ago)
• Last Synced: 2024-11-06T09:49:14.390Z (about 2 months ago)
• Topics: count, inference, python, statistics
• Language: Python
• Homepage: https://betabinomial.readthedocs.io/en/latest/
• Size: 704 KB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# BetaBinomial

![tests](https://github.com/muhammedhasan/betabinomial/actions/workflows/python-app.yml/badge.svg)

[![pypi](https://img.shields.io/pypi/v/betabinomial.svg)](https://pypi.python.org/pypi/betabinomial)

[![Documentation Status](https://readthedocs.org/projects/betabinomial/badge/?version=latest)](https://betabinomial.readthedocs.io/en/latest/?badge=latest)

Implementation of Beta-Binomial (https://en.wikipedia.org/wiki/Beta-binomial_distribution) in python for parameters inference with moment method estimation and statistical testing on count data.

[Documentation](https://betabinomial.readthedocs.io/en/latest/)

## Installation

```

pip install betabinomial

```

## Example

```python

import numpy as np

from betabinomial import BetaBinomial, pval_adj

bb = BetaBinomial()

# total counts

n = np.array([

  [5, 2, 5, 6, 6],

  [8, 8, 0, 9, 1],

  [8, 2, 6, 1, 7]

])

# event count

k = np.array([

  [3, 1, 4, 1, 2],

  [8, 7, 0, 9, 1],

  [0, 0, 0, 0, 2]

])

# Infer `alpha` and `beta` parameters from counts

bb.infer(k, n)

bb.alpha

# [[ 11.45811965]

#  [121.01628682]

#  [0.43620744]]

bb.beta

# [[13.332114  ]

#  [ 4.97492014]

#  [ 5.41047636]]

# Statistical testing with inferred `alpha` and `beta`

pval = bb.pval(k, n, alternative='two-sided')

# array([[0.33287737, 0.44653957, 0.06266123, 0.35378069, 0.85568061],

#        [0.        , 0.53825136, 0.        , 0.        , 0.        ],

#       [0.67209923, 0.26713023, 0.57287758, 0.14921533, 0.10535054]])

# Adjust p-value with multiple testing correction

padj = pval_adj(pval)

# array([[0.53067103, 0.60891759, 0.18798369, 0.53067103, 0.85568061],

#        [0.        , 0.6610126 , 0.        , 0.        , 0.        ],

#        [0.72010631, 0.50086919, 0.6610126 , 0.31974714, 0.26337634]])

```

## Citation

If you use this package in academic publication, please cite:

```

@article{celik2022analysis,

  title={Analysis of alternative polyadenylation from long-read or short-read RNA-seq with LAPA},

  author={Celik, Muhammed Hasan and Mortazavi, Ali},

  journal={bioRxiv},

  year={2022},

  publisher={Cold Spring Harbor Laboratory}

}

```