AI Article Synopsis
- Large-scale sequencing studies need effective visualization tools for genomic data linked to diverse patient traits, often using co-mutation plots.
- CoMut is a newly developed Python package that allows for the creation of customizable comutation plots from various input data types, providing a solution where current tools fall short.
- CoMut is open source, available on GitHub under the MIT License, and can be easily accessed via Google Colab for users who prefer a no-installation option.
Article Abstract
Motivation: Large-scale sequencing studies have created a need to succinctly visualize genomic characteristics of patient cohorts linked to widely variable phenotypic information. This is often done by visualizing the co-occurrence of variants with comutation plots. Current tools lack the ability to create highly customizable and publication quality comutation plots from arbitrary user data.
Results: We developed CoMut, a stand-alone, object-oriented Python package that creates comutation plots from arbitrary input data, including categorical data, continuous data, bar graphs, side bar graphs and data that describes relationships between samples.
Availability And Implementation: The CoMut package is open source and is available at https://github.com/vanallenlab/comut under the MIT License, along with documentation and examples. A no installation, easy-to-use implementation is available on Google Colab (see GitHub).
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520041 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/btaa554 | DOI Listing |
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