sbmutils 0.2.2

A collection of utility functions for data analysis

sbmutils

A collection of utility functions for data analysis.

Installation

pip install sbmutils

Usage

Quantile Normalization

import numpy as np
from sbmutils.norm import quantilenorm

# Create sample data
data = np.random.rand(10, 3)  # 10 rows, 3 columns

# Perform quantile normalization
normalized_data = quantilenorm(data, average="mean")

Features

• quantilenorm: Performs 2D quantile normalization over columns
  • Supports both mean and median averaging methods
  • Handles missing values (NaN)
  • Input validation and error handling

Requirements

• Python >= 3.6
• NumPy
• SciPy

License

This project is licensed under the MIT License.