PT  - JOURNAL ARTICLE
AU  - Frank Hidalgo
AU  - Sage Templeton
AU  - Che Olavarria Gallegos
AU  - Joanne Wang
TI  - Mutagenesis-visualization: analysis of site saturation mutagenesis datasets in Python
AID  - 10.1101/2021.10.08.463725
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.10.08.463725
4099  - http://biorxiv.org/content/early/2021/10/20/2021.10.08.463725.short
4100  - http://biorxiv.org/content/early/2021/10/20/2021.10.08.463725.full
AB  - Summary Site saturation mutagenesis (SSM) experiments have been transformative in our study of protein function. Despite the rich data generated from such experiments, current tools for processing, analyzing, and visualizing the data offer only a limited set of static plots that are difficult to customize. Furthermore, usage of the tools requires extensive experience and programming. This slows the research process for those in the biological field who are unfamiliar with programming. Here, we introduce mutagenesis-visualization, a Python API for the creation of publication-quality figures for SSM datasets which requires no prior Python or statistics experience. The plots can be rendered as native matplotlib objects (easy to stylize) or as Plotly objects (interactive graphs). Additionally, the software offers the possibility to visualize the datasets on Pymol.Availability and implementation The software can be installed from PyPI or GitHub using the pip package manager and is compatible with Python ≥ 3.8. The documentation can be found at readthedocs and the source code can be found on GitHub.Competing Interest StatementThe authors have declared no competing interest.