A Python library designed for the preprocessing, analysis and visualization of somatic genetic variants in standard formats such as VCF and MAF.
pip install pymut-bioNote: 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.
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-bioThe 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.
- Complete Documentation - Comprehensive guides and API reference
- Installation Guide - Detailed installation instructions
- API Reference - Complete API documentation
- Examples - Real-world usage examples
| 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 |
This project is licensed under the MIT License - see the LICENSE file for details.
| 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 | ✓ | ✓ |