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

Project description

omiBio

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

Latest Version Python 3.9+ License: MIT flake8

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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_fasta(), write_fasta()
omibio.analysis Sequence analysis functions GC_content(), sliding_gc(), find_orfs()
omibio.utils General-purpose utility functions truncate_repr()
omibio.viz Simple and easy-to-use data visualization plot_orf(), plot_sliding_gc()
omibio.cli Command-line interfaces for common workflows omibio orf, omibio clean

Usage example / 使用示例

Creating a sliding window GC chart using omiBio:

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

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

# Visualize easily
result.plot(show=True)  # or: plot_sliding_gc(result, show=True)

Or even one-liner:

sliding_gc(read_fasta("examples/example.fasta")["example"]).plot(show=True)

The above code will produce results like this:

Example

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:

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