omibio 0.1.2.post2

A lightweight and easy-to-use python bioinformatics toolkit.

omiBio

- A Lightweight Bioinformatics Toolkit / 轻量生信工具包

Introduction / 简介

omiBio is a lightweight, user-friendly Python toolkit for bioinformatics — ideal for education, research, and rapid prototyping.

Key features:

• Robust data structures: Sequence, Polypeptide, Gene, Genome, etc., with optional validation.
• Simple I/O: Read/write bioinformatics files (e.g., FASTA) with one-liners.
• Analysis tools: GC content, ORF detection, consensus sequences, sliding windows, and more.
• CLI included: Run common tasks from the terminal .
• Basic visualization: Built-in plotting (via matplotlib & seaborn) for quick insights.
• Functional & OOP APIs: Use classes or convenient wrapper functions.

Modules Overview / 模块概览

The omiBio toolkit is organized into the following modules:

Module	Purpose	Key Classes / Functions
omibio.sequence	Sequence-type data structures	Sequence, Polypeptide
omibio.bioObjects	Biological objects and data containers	SeqInterval, Gene, Genome
omibio.io	File I/O for common bioinformatics formats	read(), write()
omibio.analysis	Sequence analysis functions	GC_content(), sliding_gc(), find_orfs()
omibio.utils	General-purpose utility functions	Wrappers, helper functions
omibio.viz	Simple and easy-to-use data visualization	plot_orf(), plot_sliding_gc()
omibio.cli	Command-line interfaces for common workflows	omibio orf, other CLI commands

Usage example / 使用示例

Creating a sliding window GC chart using omiBio:

from omibio.io import read
from omibio.analysis import sliding_gc
from omibio.viz import plot_sliding_gc, plt

# Load sequences from FASTA (returns dict[str, Sequence])
seq_dict = read("examples/example.fasta")
dna: Sequence = seq_dict["example"]

# Compute GC content in sliding windows (window=200 bp, step=20 bp)
gc_list = sliding_gc(dna, window=200, step=20)

# Visualize easily
plot_sliding_gc(gc_list, seq=dna, window_avg=True)
plt.show()

The above code will produce results like this:

Using omiBio's Command-line interfaces:

$ omibio orf example.fasta --min-length 100

The above CLI will produce results like this:

# Seq-name  start    end   strand   frame   length
example_2    70      289     -       -2      219
example_16   53      257     +       +3      204
example_13   118     301     +       +2      183
example_4    92      272     -       -1      180
example_2    157     322     +       +2      165
example_5    17      173     -       -1      156
example_16   176     332     -       -1      156
...

Installation / 安装

From PyPI:

$ pip install omibio

Requirements

• Python: >= 3.9
• Core dependencies:
  • click (for CLI)
  • numpy & pandas (analysis/plotting dependencies)
• Optional dependencies (install for extra features):
  • matplotlib & seaborn → enables visualization

Optional deps won't be installed by default. To get them:

pip install omibio[plot]

For complete project build and dependency configuration, please refer to pyproject.toml

Code Style

omiBio follows PEP 8 conventions for Python code.
All code is automatically formatted and checked using flake8.

License

This project is licensed under the MIT License.

Things to note

• Most of the code in this project uses 0-based indexes, half-open interval, rather than the 1-based indexes commonly used in biology.
• All code type hints in this project use PEP 585 generic syntax in Python 3.9+.
• This project is still under development and not yet ready for production. Please use it with caution. If you have any suggestions, please contact us:
  • gmail: [e-mail]
  • qq: 2658592119