Mutagenesis_visualization is a Python package aimed to generate publication-quality figures for site-saturation mutagenesis datasets.
The package main focus is to perform the processing, statistical analysis and visualization steps of your pipeline, but it additionally offers tools to calculate enrichment scores from FASTQ files.
- Calculate enrichment scores from FASTQ files, allowing for different ways of data processing and normalization.
- Produce publication-quality heatmaps from enrichment scores as well as a wide range of visualization plots.
- Principal component analysis (PCA), hierarchical clustering and receiver operating characteristic (ROC) curve tools.
- Map enrichment scores effortlessly onto a PDB structure using Pymol. Structural properties such as SASA, B-factor or atom coordinates can be extracted from the PDB and visualized using a built-in method.
- Generate dashboards.
Mutagenesis Visualization can be installed from PyPI by executing:
pip install mutagenesis_visualization
If you prefer to install from Github, use:
pip install git+https://github.com/fhidalgor/mutagenesis_visualization
If you use the software, please, cite our publication.
You can find the documentation here.
There are 7 jupyter notebooks in the folder mutagenesis_visualization/tutorial that go through the basics on how to use the software. You can play with them online via mybinder without having to download anything.
If you wish to contribute to the software, branch it, add the new feature and then do a PR. If you find bugs in the code, you can either report them under Issues, or fix them by yourself with a PR.