pymut-bio 0.1.9

A Python library for genetic mutations

pyMut 🧬

A Python library designed for the preprocessing, analysis and visualization of somatic genetic variants in standard formats such as VCF and MAF.

🚀 Quick Start

Installation

Option 1: Basic Installation (pip)

pip install pymut-bio

Note: The pip installation provides core functionality for mutation data visualization, but some advanced features may be limited as certain bioinformatics tools are not available through PyPI.

Option 2: Full Installation (Recommended - Conda)

For complete functionality including all bioinformatics tools, use the conda environment:

# 0) Descargar el environment.yml (elige curl o wget)
curl -fsSL https://raw.githubusercontent.com/Luisruimor/pyMut/main/environment.yml -o environment.yml
# ó:
# wget -O environment.yml https://raw.githubusercontent.com/Luisruimor/pyMut/main/environment.yml

# 1) crear el entorno (añade tus binarios al environment.yml)
conda env create -f environment.yml

# 2) activar el entorno
conda activate NOMBRE-DEL-ENTORNO

# 3) instalar tu librería desde PyPI en ese entorno
pip install pymut-bio

The conda environment includes essential bioinformatics tools:

• bcftools: VCF/BCF file manipulation
• ensembl-vep: Variant Effect Predictor
• htslib: High-throughput sequencing data processing
• tabix: Generic indexer for TAB-delimited genome position files

These tools enable advanced genomic data processing capabilities that are not available with pip-only installation.

📚 Documentation

• Complete Documentation - Comprehensive guides and API reference
• Installation Guide - Detailed installation instructions
• API Reference - Complete API documentation
• Examples - Real-world usage examples

📋 Requirements

Librería	Dependencias inmediatas
duckdb 1.3.2	– Ninguna
fastparquet 2024.11.0	– cramjam ≥ 2.3 – fsspec – numpy – packaging – pandas ≥ 1.5.0
matplotlib 3.10.3	– contourpy ≥ 1.0.1 – cycler ≥ 0.10 – fonttools ≥ 4.22.0 – kiwisolver ≥ 1.3.1 – numpy ≥ 1.23 – packaging ≥ 20.0 – pillow ≥ 8 – pyparsing ≥ 2.3.1 – python-dateutil ≥ 2.7
mkdocs 1.6.1	– click ≥ 7.0 – colorama ≥ 0.4 – ghp-import ≥ 1.0 – jinja2 ≥ 2.11.1 – markdown ≥ 3.3.6 – markupsafe ≥ 2.0.1 – mergedeep ≥ 1.3.4 – mkdocs-get-deps ≥ 0.2.0 – packaging ≥ 20.5 – pathspec ≥ 0.11.1 – pyyaml ≥ 5.1 – pyyaml-env-tag ≥ 0.1 – watchdog ≥ 2.0
numpy 1.26.4	– Ninguna
pandas 2.3.1	– numpy ≥ 1.22.4 – python-dateutil ≥ 2.8.2 – pytz ≥ 2020.1 – tzdata ≥ 2022.7
pyarrow 14.0.2	– numpy ≥ 1.16.6
pyensembl 2.3.13	– datacache ≥ 1.4.0,<2.0.0 – gtfparse ≥ 2.5.0,<3.0.0 – memoized-property ≥ 1.0.2 – pylint ≥ 2.17.2,<3.0.0 – serializable ≥ 0.2.1,<1.0.0 – tinytimer ≥ 0.0.0,<1.0.0 – typechecks ≥ 0.0.2,<1.0.0
pyfaidx 0.8.1.4	– packaging
requests 2.32.4	– certifi ≥ 2017.4.17 – charset-normalizer ≥ 2,<4 – idna ≥ 2.5,<4 – urllib3 ≥ 1.21.1,<3
scikit-learn 1.7.1	– joblib ≥ 1.2.0 – numpy ≥ 1.22.0 – scipy ≥ 1.8.0 – threadpoolctl ≥ 3.1.0
scipy 1.11. 4	– numpy ≥ 1.21.6,<1.28.0
seaborn 0.13.2	– matplotlib ≥ 3.4,<3.6.1 or >3.6.1 – numpy ≥ 1.20,<1.24.0 or >1.24.0 – pandas ≥ 1.2
urllib3 2.5.0	– Ninguna

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🎯 Comparison with Other Tools

FUNCTIONAL CRITERIA	PYMUT (PROPOSAL)	MUTSCAPE	MAFTOOLS
Input formats	VCF & MAF (native)	MAF	MAF
VEP annotation	✓
Genomic range filtering	✓	✓	✓
PASS category variant filtering	✓	✓
Sample filtering	✓		✓
Tissue expression filtering	✓	✓
File format transformation	✓	✓ (VCF to MAF only)	✓ (VCF to MAF only)
File combination	✓	✓
Significantly mutated genes (SMG) detection		✓
Cancer-related gene annotation	✓	✓
Tumor mutational burden (TMB) calculation	✓	✓
Mutational signature identification	✓
Medical implications mutation annotation	✓	✓
PFAM annotation support	✓		✓
Summary Plot	✓		✓
Oncoplot	✓		✓
Lollipop Plot	✓		✓
Somatic Interactions Plot	✓		✓
Mutational Signature Analysis	✓	✓
CoMut Plot	✓	✓