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A Python library for genetic mutations

Project description

pyMut 🧬

Python 3.10+ License: MIT PyPI version

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-Library

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/Molecular-Oncology-Group-UFV/PyMut/main/environment.yml -o environment.yml
# ó:
# wget -O environment.yml curl -fsSL https://raw.githubusercontent.com/Molecular-Oncology-Group-UFV/PyMut/main/environment.yml -o 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-Library

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

📋 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

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